WO2019085075A1

WO2019085075A1 - Information element set generation method and rule execution method based on rule engine

Info

Publication number: WO2019085075A1
Application number: PCT/CN2017/112514
Authority: WO
Inventors: 宋杰; 赵骏
Original assignee: 平安科技（深圳）有限公司
Priority date: 2017-10-31
Filing date: 2017-11-23
Publication date: 2019-05-09
Also published as: CN107862328A

Abstract

An information element set generation method. The method comprises: obtaining original information elements in each original information element set; performing similarity calculation on every two original information elements to generate corresponding original similarities; and extracting independent information elements in the multiple original information elements according to the multiple original similarities to generate an independent information element set, the original similarity between any two independent information elements in the independent information element set being less than a preset similarity threshold.

Description

Information element set generation method and rule execution method based on rule engine

This application claims the priority of the Chinese patent application filed on October 31, 2017, the Chinese Patent Office, the application number is 201711043201X, and the invention name is "information element set generation method and rule engine based rule execution method". The citations are incorporated herein by reference.

Technical field

The present invention relates to the field of computer information management technologies, and in particular, to a method, an apparatus, a storage medium, and a computer device for generating an information element set, and a rule execution method, apparatus, storage medium, and computer device based on a rule engine.

Background technique

The rules engine is developed by the inference engine and is a component embedded in the application. Implements the separation of business decisions from application code and uses predefined semantic modules to write business decisions. Accept data input, interpret business rules, and make business decisions based on business rules. An information element is the basic building block of the rules engine. It is an object that contains all the information about a particular event. The rule engine receives the information elements sequentially from the queue manager, and then executes the rules carried by the information elements in the order defined by the rules.

However, in a traditional information element set, when there are a large number of information elements, there may be partially repeated or all repeated information elements, and the redundant information elements waste resources, resulting in more efficient execution of the rules contained in the information elements by the rules engine. low.

Summary of the invention

According to various embodiments of the present application, an information element set generation method, apparatus, storage medium, and computer apparatus are provided.

According to various embodiments of the present application, a rule execution method based on a rule engine is provided, and Storage, storage media, and computer equipment.

An information element set generation method includes: acquiring an original information element in each original information element set; performing similarity calculation on each two original information elements to generate a corresponding original similarity; and extracting according to multiple original similarities An independent information element in the plurality of original information elements is generated, and an independent information element set is generated, and an original similarity of any two independent information elements in the independent information element set is less than a preset similarity threshold.

A rule execution method based on a rule engine, comprising: acquiring a set of independent information elements, wherein the set of independent information elements is generated according to the information element set generation method described in the foregoing embodiments; acquiring a queue of information elements to be matched, The to-be-matched information element queue includes a plurality of original information elements; and each original information element in the to-be-matched information element queue is matched with an independent information element in the independent information element set, and the to-be-executed information is generated according to the matching result. a meta-queue; executing, by the rule engine, a rule included in the independent information element in the to-be-executed information element queue.

An information element set generating apparatus, comprising: an original information element acquiring module, configured to acquire an original information element in each original information element set; and a original similarity generating module, configured to The original information element performs similarity calculation to generate a corresponding original similarity; and the independent information element set generating module is configured to extract independent information elements in the plurality of original information elements according to the multiple original similarities, and generate an independent information element set. The original similarity of any two independent information elements in the set of independent information elements is less than a preset similarity threshold.

A rule execution engine-based rule execution device, comprising: an independent information element set acquisition module, configured to acquire an independent information element set, wherein the independent information element set is according to the information described in the foregoing embodiments. a meta-collection generating method is configured to obtain a to-be-matched information element queue, wherein the to-be-matched information element queue includes a plurality of original information elements; the to-be-executed information element queue generation module is used to Each of the original information elements in the matching information element queue is matched with the independent information element in the independent information element set, and the information element queue to be executed is generated according to the matching result; and the rule execution module is configured to execute the rule engine The rules contained in the independent information element in the execution information element queue are described.

One or more non-volatile readable storage media storing computer readable instructions for said computing When the machine readable instructions are executed by one or more processors, causing the one or more processors to perform the steps of: acquiring the original information elements in each of the original information element sets; performing similarity for each of the two original information elements Calculating, generating a corresponding original similarity; and extracting independent information elements in the plurality of original information elements according to the plurality of original similarities, generating an independent information element set, and any two independent information elements in the independent information element set The original similarity is less than the preset similarity threshold.

One or more non-transitory readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the steps of: acquiring a set of independent information elements, the independent information element set is generated according to the information element set generation method described in the foregoing embodiments; and the information element queue to be matched is obtained, where the information element queue to be matched includes a plurality of original information elements; Each original information element in the to-be-matched information element queue is matched with an independent information element in the independent information element set, and a to-be-executed information element queue is generated according to the matching result; and the to-be-executed information element is executed by a rule engine The rules contained in the independent information element in the queue.

A computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The following steps: obtaining original information elements in each original information element set; performing similarity calculation on each of the two original information elements to generate corresponding original similarity; and extracting multiple original information elements according to multiple original similarities The independent information element generates an independent information element set, and the original similarity of any two independent information elements in the independent information element set is less than a preset similarity threshold.

A computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The following steps: obtaining an independent information element set, the independent information element set is generated according to the information element set generation method described in the foregoing embodiments; acquiring a to-be-matched information element queue, where the to-be-matched information element queue includes multiple originals Information element; matching each original information element in the to-be-matched information element queue with an independent information element in the independent information element set, generating a to-be-executed information element queue according to the matching result; and performing the Pending information The rules contained in the independent information element in the meta-queue.

Details of one or more embodiments of the present application are set forth in the accompanying drawings and description below. Other features, objects, and advantages of the invention will be apparent from the description and appended claims.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings to be used in the embodiments will be briefly described below. Obviously, the drawings in the following description are only some embodiments of the present application, Those skilled in the art can also obtain other drawings based on these drawings without any creative work.

1 is an application environment diagram of a method for generating an information element set in an embodiment;

2 is a flowchart of a method for generating an information element set in an embodiment;

3 is a schematic diagram of information element generation and processing in an embodiment;

4 is a flowchart of a method for generating an information element set in another embodiment;

5 is a flowchart of a rule execution method based on a rule engine in an embodiment;

6 is a flow chart of a rule execution method based on a rule engine in another embodiment;

7 is a flowchart of a rule execution method based on a rule engine in still another embodiment;

FIG. 8 is a structural block diagram of an information element set generating apparatus in an embodiment; FIG.

9 is a structural block diagram of a rules execution apparatus based on a rule engine in an embodiment;

Figure 10 is a diagram showing the internal structure of a computer device in one embodiment.

Detailed ways

In order to make the objects, technical solutions, and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.

It will be understood that the terms "first", "second" and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the application, The first information element is referred to as a second information element, and similarly, the second information element may be referred to as a first information element. Both the first information element and the second information element are information elements, but they are not the same information element.

The method for generating an information element set provided by the embodiment of the present application can be applied to an application environment as shown in FIG. 1 . Referring to FIG. 1, the application environment includes a server 102 and a plurality of terminals 104. The server may be an independent physical server or a server cluster composed of multiple physical servers, and the terminal may be a mobile phone, a tablet computer, a personal digital assistant, or a smart device. The server 102 can be configured to execute the information element set generation method and the rule engine based rule execution method provided by the embodiments of the present application. The server device 102 can be connected to the network of the terminal 104, including but not limited to a wireless network, a wired network, and the like. For example, server 102 can obtain a collection of original information elements in terminal 104 over a network connection.

In an embodiment, as shown in FIG. 2, an information element set generation method is provided, which can be used in the server 102 in the application environment as shown in FIG. 1, the method includes:

Step S202: Acquire original information elements in each original information element set.

In this embodiment, the original information element refers to a pre-existing information element. The information element is an object that contains all the information of a specific event, including but not limited to: a message, an application identifier that generates an event, an event generation event, an information element type, a related rule set, a general method, a general attribute, and some System related information, etc. FIG. 3 is a schematic diagram of information element generation and processing. As shown in FIG. 3, each information element has a corresponding information service, and the information service generates a specific information element by using the rules stored in the facts and rules. The rule engine sequentially receives information elements from the queue manager, detects rules in the information elements, and implements the rules. Among them, the rule is a method of describing the business logic. The rule consists of two parts: the condition filter and the action. When the program runs, the action is executed when the condition filter is true. Rules can be defined by language and stored in a rule set. The rule engine is an engine that performs the actions specified in the rules based on the filtering conditions contained in the rules and determines whether they match the real-time conditions of the running time. The original information element set refers to a set composed of a plurality of original information elements.

In one embodiment, the server may obtain a corresponding set of original information elements from a plurality of terminals, respectively. Each of the original information element sets includes one or more original information elements.

Step S204, performing similarity calculation on each of the two original information elements to generate a corresponding original similarity.

In this embodiment, the information included in the original information element is calculated according to a preset similarity algorithm. The similarity algorithm includes, but is not limited to, a distance-based calculation method and a calculation method based on a similarity measure, such as an Euclidean Distance, a Manhattan Distance, a Minkowski Distance, Chebyshev Distance and Cosine Similarity, Pearson Correlation Coefficient, etc. The information contained in the original information element includes, but is not limited to, information element types, rules, and general attributes.

In one embodiment, each original information element includes a rule, and the similarity calculation of the rules included in the two original information elements may be performed by using a preset similarity algorithm formula to generate original similarity of the two rules. .

Step S206, extracting independent information elements in the plurality of original information elements according to the plurality of original similarities, and generating an independent information element set.

In this embodiment, the independent information element refers to an information element that is independent of any other independent information element, that is, the similarity between any two independent information elements is less than a preset threshold. A set of independent information elements refers to a set of independent information elements extracted. After calculating the original similarity between each two original information elements in all the original information elements, the original information element whose original similarity with any other original information element is less than the preset threshold may be used as the independent information element.

In an embodiment, two or more original information elements whose original similarity is greater than a preset similarity threshold may be combined to generate one combined information element, and the combined information element may be used as an independent information element.

For example, the rules contained in multiple original information elements are as shown in Table 1:

For rules 1 and 2 with similarity greater than the preset similarity threshold, since the undergraduate and above of the rule includes graduate students, the information element including rule 1 may be extracted as an independent information element; for the similarity is greater than the preset similarity Rules 3 and 4 of the threshold, since the credits of 50 or more and 50 or less are not available for the specialists and the following users, a new independent information element can be combined, and the included rule 5 can be if the user qualification is a specialist. And below, you can not borrow. An independent set of information elements can be generated according to the independent information elements corresponding to rules 1 and 5.

In the foregoing embodiment, after acquiring the pre-existing original information element, the similarity information in the original information element is filtered by performing similarity calculation on each of the two original information elements, and the independent information element set is regenerated according to the independent information element. . The redundant original information elements in the pre-existing original information element set are eliminated, which saves system resources.

In an embodiment, the independent information elements in the plurality of original information elements are extracted according to the plurality of original similarities, and after the independent information element set is generated, the independent information element set may also be divided into the general information element set and the special information element set. . After the similarity calculation is performed for each of the two original information elements, and the corresponding original similarities are generated, each original information element has a original similarity corresponding to other original information elements. The original similarity corresponding to each independent information element may be counted, and the number of original similarities greater than the preset similarity threshold is generated, and the independent information element whose number is greater than the preset threshold generates a common information element set, and the quantity is less than the pre-predetermined The independent information element of the threshold is generated to generate a special information element set.

In an embodiment, the independent information element in the plurality of original information elements is extracted according to the plurality of original similarities, and after the generating the independent information element set, the method further includes: acquiring the newly added information element that needs to be added; Performing similarity calculation on each independent information element in the set of independent information elements, generating corresponding new similarity; determining whether there is new similarity greater than the preset similarity threshold; if yes, adding the new information element If not, the added information element is added as an independent information element to the independent information element set.

In one embodiment, as shown in FIG. 4, step S204 includes:

Step S402, extracting original keywords in each original information element.

In this embodiment, the original keyword refers to the vocabulary used in defining the rules in the information element. For example, age, gender, education, income, and property value.

In an embodiment, step S402 includes: segmenting each original information element according to a preset word segmentation algorithm to generate a corresponding plurality of original words; and presetting each original information element with a preset keyword library The original words of the keyword match are used as the original keywords.

The preset word segmentation algorithm includes, but is not limited to, a combination algorithm based on one or more of a word segmentation based segmentation method, an understanding based segmentation method, and a statistics based segmentation method. The original information element is segmented according to a preset word segmentation algorithm, and the continuous word sequence in the rule included in the original information element can be recombined into a word sequence according to a certain specification. The original words included in the word sequence can be matched with the preset keywords in the preset keyword library, and the matched original words are used as the original keywords.

In one embodiment, after each original information element is segmented according to a preset word segmentation algorithm to generate a corresponding plurality of original words, the method further includes removing the stop words in the original words. The original words are matched with the stop words in the preset stop word database, and the matched stop words are filtered from the recombined word sequence. For example, stop words can be words such as "this", "", "such as", and can also be punctuation and the like. Further, the original keyword may also be determined according to the frequency corresponding to the original word filtered by the stop word. It can be calculated according to the formula: P=N/m, and the frequency P of each original word after the stop word filtering is obtained, where N is the frequency of occurrence of the original word, m is the total number of words in the word database, and the frequency is greater than the pre- Set the original word of the threshold as the original keyword.

Step S404, acquiring preset keyword weights corresponding to each original keyword.

In this embodiment, the preset keyword weight is a weight that reflects the importance of the keyword. Since the more personalized keyword indicates that the keyword can reflect the business characteristics of the corresponding rule, the more important the keyword is, the more important the keyword is, the less important it is. Therefore, the keyword with higher popularity can be given correspondingly. Low default keyword weights.

In an embodiment, the calculation may be performed according to the formula: W=log(D/D _W ), and the preset keyword weights of each keyword are obtained, where W is a preset keyword weight, and D is all originals. The total number of rules contained in the information element, D _W is the number of rules containing the keyword. For example, the number of rules containing the keyword "education" is 100, and the total number of rules included in all information elements is 1000, then W=log(1000/100), and the default keyword weight is 1.

Step S406: Generate an original information element vector with each original information element according to a preset keyword weight corresponding to each original information element.

In this embodiment, each original information element may include one or more original keywords. Each original keyword corresponds to a preset keyword weight, and a vector space model may be constructed according to one or more preset keyword weights corresponding to each original information element, and a primitive corresponding to the original information element is generated. Information element vector.

For example, if the rule R contains n original keywords, the rule R _x can be expressed as an n-dimensional vector R _x (R _x1 , R _x2 , R _x3 ... ... R _xn ), where R _x1 to R _xn are n eigenvalues. The rule R _x may also be expressed as an n-dimensional vector R _x (W ₁ , W ₂ , W ₃ . . . W _n ) of the predetermined keyword weight corresponding to each original keyword, wherein W ₁ to W _n is the preset keyword weight corresponding to each original keyword.

Step S408, performing similarity calculation on the original information element vector corresponding to each of the two original information elements, and generating corresponding original similarity.

In this embodiment, the original similarity refers to the similarity calculated according to a preset similarity algorithm according to any two original information element vectors.

In an embodiment, when the similarity calculation is performed on the original information element vector corresponding to the two original information elements, the feature items in the two original information element vectors may be correspondingly matched, and the feature items that cannot be corresponding are marked as presets. Value, such as 0. For example, for the similarity calculation of two original information element vectors of R ₁ (a, b, c, d) and R ₂ (a, c, d, e), since there is no e in R ₁ , R ₂ Without b, the non-corresponding feature items can be marked as 0. Therefore, the two original information element vectors can be converted into R ₁ (a, b, c, d, 0) and R ₂ (a, 0, c, respectively). After d, e), the similarity calculation is performed.

In one embodiment, step S408 includes: a first information element vector corresponding to each two original information elements

Second information element vector

According to the formula

Perform similarity calculations to generate corresponding original similarities

Where W _0k is the first information element vector

Corresponding n preset keyword weights, W _Ak is the second information element vector

The corresponding n preset keyword weights.

In this embodiment, the similarity algorithm used is an algorithm for calculating the cosine similarity of vector space. After generating the original information element vector corresponding to the plurality of original information elements, the similarity calculation is performed on any two original information element vectors. For example, for

and

Three information element vectors, need to be targeted

versus

The similarity calculation is performed separately to generate three corresponding original similarities. Wherein, the original similarity value may be 0 to 1, and the closer the value of the original similarity is to 0, the lower the similarity between the two original information element vectors, and the closer the original similarity value is to 1, indicating the two original information element vectors. The higher the similarity.

In an embodiment, after performing the similarity calculation on each of the two original information elements to generate the corresponding original similarity, the method further includes: determining whether the original similarity is less than a preset similarity threshold. If yes, it may be determined that the two original information elements corresponding to the original similarity less than the preset similarity threshold are duplicate original information elements. One of the plurality of original information elements that are repeated may be extracted as an independent information element. For example, when the first information element vector

Second information element vector

Corresponding original similarity

When the preset similarity threshold is greater than 0.9, the first information element vector may be extracted.

Corresponding first information element or second information element vector

The corresponding second information element is used as an independent information element.

In the above embodiment, the original information element vector of the original information element is generated by extracting the original keyword in the original information element and according to the preset keyword weight corresponding to the original keyword. Any two original information element vectors are calculated according to a preset similarity algorithm, and corresponding original similarities are generated, and independent information elements are determined according to the original similarity, so that redundant information elements can be accurately eliminated.

In an embodiment, as shown in FIG. 5, a rules engine-based rule execution method is provided, and the method includes:

Step S502, acquiring a set of independent information elements.

In this embodiment, the set of independent information elements may be a set of information elements generated by the information element set generation method provided according to the foregoing various embodiments. The independent information element set includes multiple independent information elements, and the original similarity of any two independent information elements is less than a preset similarity threshold.

Step S504, obtaining a queue of information to be matched.

In this embodiment, the information element queue to be matched refers to an information element queue corresponding to the original information element set and including a plurality of original information elements. The information element in the information element queue has a preset execution order, and the queue management can be performed through the queue manager in FIG. 3 .

In an embodiment, for each service, a corresponding information element queue to be matched may be preset. For example, for service A, a queue of information to be matched containing n original information elements may be preset, and R _A1 , R _A2 , R _{A3 ,} ... R _An , R _A1 to R _An are original information elements in service A.

Step S506: Match each original information element in the information element queue to be matched with the independent information element in the independent information element set, and generate a to-be-executed information element queue according to the matching result.

In this embodiment, the to-be-executed information element queue refers to an information element queue corresponding to the to-be-matched information element queue generated according to the independent information element in the independent information element set. The independent information element included in the to-be-executed queue has a one-to-one correspondence with the original information element in the information element queue to be matched.

Step S508, executing, by the rule engine, a rule included in the independent information element in the information element queue to be executed.

In this embodiment, the rule engine is a component embedded in an application and is an environment in which rules are executed. As shown in Figure 3, the rules engine can receive information elements in turn from the queue manager. The information element may include one or more rules, and the rule engine may check the first rule included in the information element according to a preset order, and evaluate the condition filter. If the value is false, all the rules are related to the rule. The actions are ignored and continue to execute the next rule; if the value is true, the actions related to this rule are executed sequentially, and the next rule is executed after execution. After all the rules in the information element have been executed, the information element will be destroyed and the next information element will be received from the queue manager.

In the foregoing embodiment, the original information element in the information element queue to be matched is matched with the independent information element in the independent information element set, and the information element queue to be executed is regenerated, and the rule is introduced by rules. The engine executes the rules contained in the independent information element in the information element queue to be executed, thereby avoiding the repeated execution of the rules in the redundant information element, thereby improving the efficiency of the rule execution.

In an embodiment, as shown in FIG. 6, step S506 includes:

Step S602: Perform similarity calculation on each original information element in the queue of the information to be matched and the independent information element in the independent information element set to generate a corresponding matching similarity.

In this embodiment, the matching similarity is a similarity generated by the pointer to calculate the original information element and the independent information element according to a preset similarity algorithm. Corresponding to step S204, the information included in each of the original information element and the independent information element in the independent information element set may be calculated according to a preset similarity algorithm to generate a corresponding matching similarity. The similarity algorithm includes, but is not limited to, a distance-based calculation method and a similarity degree-based calculation method.

In one embodiment, according to the formula

First information element vector corresponding to the original information element

Second information element vector corresponding to the independent information element

Perform similarity calculation to generate corresponding matching similarity

Where W _0k is the first information element vector

The corresponding n preset keyword weights.

Step S604, the independent information element corresponding to the matching similarity greater than the preset similarity threshold is used as the independent information element matching the corresponding original information element.

In this embodiment, after detecting the independent information element whose matching similarity with the original information element is greater than the preset similarity threshold, the independent information element corresponding to the matching similarity of the preset similarity threshold may be used as the The independent information element matched by the original information element, and stops the similarity calculation of the original information element and other independent information elements.

In an embodiment, each original information element may be similarly calculated with each independent information element to generate a matching similarity between the original information element and each independent information element, and the maximum matching similarity is independent. The information element acts as an independent information element that matches the corresponding original information element.

Step S606: Generate, according to the independent information element matched with each original information element, a to-be-executed information element queue corresponding to the information element queue to be matched.

In this embodiment, after obtaining the independent information element in the set of independent information elements that matches the original information element in the information element queue to be matched, the corresponding information source queue to be executed may be generated according to the matched independent information element.

For example, for service A, a queue of information to be matched containing n original information elements may be preset, and R _A1 , R _A2 , R _{A3 ,} ... R _An , R _A1 to R _An are original information elements in service A. If it is detected that the independent information element matching R _A1 in the independent information element set is R ₁ , the independent information element matching R _A2 is R ₂ , and the independent information element matching R _A3 is R ₃ ... matching with R _An The independent information element is R _k , and R ₁ , R ₂ , R ₃ . . . R _k can be used as the to-be-executed information element queue corresponding to the information element queue to be matched.

In an embodiment, as shown in FIG. 7, step S506 includes:

Step S702, matching each original information element in the information element queue to be matched with the independent information element in the independent information element set.

In this embodiment, each original information element in the information element queue to be matched may be similarly calculated with the independent information element in the independent information element set, and the independent information element corresponding to the similarity of the similarity threshold may be used as An independent information element that matches the original information element.

Step S704, the independent information element matching the original information element is marked with a matching identifier.

In this embodiment, the matching identifier is used to mark the identifier of the independent information element in the independent information element set, and the identified independent information element matches any one of the original information elements in the information element queue to be matched. The matching identifier can be a letter or data, for example, the matching identifier can be 1.

For example, when it is detected that the first information element R _A1 in the information element queue to be matched matches the independent information element R ₁ , the independent information element may be marked as 1 and may not be matched with any original information element. The independent information element is marked as 0.

Step S706: traverse the independent information element in the independent information element set according to a preset order, and queue the to-be-executed information element generated by the independent information element marked with the matching identifier.

In this embodiment, traversing refers to performing independent detection of the independent information elements in the independent information element set in a preset order and performing only one detection. An independent information element marked with a matching identifier will be detected to be executed Line information element queue.

For example, the independent information element set includes k independent information elements, R ₁ , R ₂ , R _{3 ,} . . . R _k , after each original information element in the information element queue to be matched is matched with the independent information element. The independent information element matched with the original information element is matched with the identifier 1 to traverse all the independent information elements in the independent information element set according to a preset order, and the independent information element marked with the matching identifier 1 is detected as R ₂ , R ₆ , R ₁₁ ... R _n , then R ₂ , R ₆ , R ₁₁ ... R _{n can be} used as a queue of information elements to be executed.

In an embodiment, as shown in FIG. 8, an information element set generating apparatus 800 is provided. The apparatus includes: an original information element obtaining module 802, configured to acquire an original information element in each original information element set; The similarity generation module 804 is configured to perform similarity calculation on each of the two original information elements to generate a corresponding original similarity. The independent information element set generation module 806 is configured to extract multiple original information elements according to the multiple original similarities. The independent information element in the generated information element set, and the original similarity of any two independent information elements in the independent information element set is less than the preset similarity threshold.

In one embodiment, the original similarity generation module 804 is further configured to extract original keywords in each original information element; acquire preset keyword weights corresponding to each original keyword; and corresponding according to each original information element The preset keyword weights are generated with the original information element vector of each original information element; the similarity calculation is performed on the original original information element vector corresponding to each of the two original information elements, and the corresponding original similarity is generated.

In an embodiment, the original similarity generation module 804 is further configured to perform segmentation of each original information element according to a preset word segmentation algorithm to generate a corresponding plurality of original words; and each original information element and the preset keyword The original words in the library that match the preset keywords are used as the original keywords.

In one embodiment, the original similarity generation module 804 is further configured to use a first information element vector corresponding to each two original information elements.

Second information element vector

According to the formula

Perform similarity calculations to generate corresponding original similarities

Where W _0k is the first information element vector

Corresponding preset keyword weight, W _Ak is the second information element vector

The corresponding preset keyword weight.

In an embodiment, as shown in FIG. 9, a rule engine-based rule execution apparatus 900 is provided. The apparatus includes: an independent information element set acquisition module 902, configured to acquire an independent information element set, and the independent information element set is based on The information element set generation method 904 is configured to obtain the information element queue to be matched, and the information element queue to be matched includes a plurality of original information elements; the information element queue to be executed The generating module 906 is configured to match each original information element in the information element queue to be matched with the independent information element in the independent information element set, and generate a to-be-executed information element queue according to the matching result; the rule execution module 908 is configured to pass The rules engine executes the rules contained in the independent information elements in the information element queue to be executed.

In an embodiment, the to-be-executed information element queue generation module 906 is further configured to perform similarity calculation on each of the original information elements in the pair of matching information element queues and the independent information elements in the independent information element set, to generate corresponding matching similarities. And matching the independent information element corresponding to the similarity greater than the preset similarity threshold as the independent information element matching the corresponding original information element; generating and matching the information element according to the independent information element matched with each original information element The corresponding queue of information to be executed in the queue.

Each of the above-described information element set generation means and the rules engine-based rule execution means may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in the hardware of the terminal or may be stored in the memory of the terminal in a software form, so that the processor calls the execution of the operations corresponding to the above modules. The processor can be a central processing unit (CPU), a microprocessor, a microcontroller, or the like.

The information element set generation means and the rule engine based rule execution means described above may be embodied in the form of a computer readable instruction executable on a computer device as shown in FIG.

In one embodiment, one or more non-volatile readable storage media having computer readable instructions stored by one or more processors are provided, such that one or more processors are Perform the following steps: obtain the original information element in each original information element set; Two original information elements are used for similarity calculation to generate corresponding original similarities; independent information elements in multiple original information elements are extracted according to multiple original similarities, and an independent information element set is generated, and any two of the independent information element sets are generated. The original similarity of the independent information elements is less than the preset similarity threshold.

In one embodiment, the step of performing similarity calculation on each of the two original information elements by the processor to generate a corresponding original similarity includes the following steps: extracting original keywords in each original information element; a preset keyword weight corresponding to each original keyword; generating an original information element vector for each original information element according to a corresponding preset keyword weight of each original information element; for each two original information elements The corresponding original information element vector is used for similarity calculation to generate corresponding original similarity.

In one embodiment, the step of extracting the original keyword in each original information element performed by the processor specifically includes the following steps: segmenting each original information element according to a preset word segmentation algorithm, and generating corresponding multiple words. The original word; the original word in each original information element that matches the preset keyword in the preset keyword library is used as the original keyword.

In one embodiment, the performing, by the processor, performing a similarity calculation on the original information element vector corresponding to each two original information elements, and generating a corresponding original similarity, specifically includes the following steps: for each two original information elements Corresponding first information element vector

Second information element vector

According to the formula

Perform similarity calculations to generate corresponding original similarities

Where W _0k is the first information element vector

The corresponding preset keyword weight.

In one embodiment, there is also provided one or more non-transitory readable storage mediums storing computer readable instructions that, when executed by one or more processors, cause one or more processes The device performs the following steps: acquiring an independent information element set, and the independent information element set is generated according to the information element set generation method in each of the foregoing embodiments; acquiring a to-be-matched information element queue, where the to-be-matched information element queue includes multiple original information elements; Each original letter in the queue of information to be matched The information element is matched with the independent information element in the set of independent information elements, and the information element queue to be executed is generated according to the matching result; the rules included in the independent information element in the information element queue to be executed are executed by the rule engine.

In an embodiment, the step of matching, by the processor, the original information element in the information element queue to be matched with the independent information element in the independent information element set, and generating the information element queue to be executed according to the matching result, specifically The method includes the following steps: performing similarity calculation on each original information element in the matching information element queue and the independent information element in the independent information element set, and generating a corresponding matching similarity; the matching similarity is greater than the preset similarity threshold. The independent information element is an independent information element that matches the corresponding original information element; and the information element queue to be executed corresponding to the information element queue to be matched is generated according to the independent information element matched with each original information element.

In one embodiment, a computer apparatus is provided comprising a memory and one or more processors having stored therein computer readable instructions that, when executed by the processor, cause one or more The processor performs the following steps: acquiring the original information element in each original information element set; performing similarity calculation on each of the two original information elements to generate a corresponding original similarity; and extracting multiple original information according to the multiple original similarities The independent information element in the element generates an independent information element set, and the original similarity of any two independent information elements in the independent information element set is less than a preset similarity threshold.

Second information element vector

According to the formula

Perform similarity calculations to generate corresponding original similarities

Where W _0k is the first information element vector

The corresponding preset keyword weight.

In one embodiment, there is also provided a memory and one or more processors having stored therein computer readable instructions that, when executed by the processor, cause one or more processors to perform the following Step: Acquire an independent information element set, and the independent information element set is generated according to the information element set generation method in each embodiment; obtain the information element queue to be matched, and the to-be-matched information element queue includes multiple original information elements; Each original information element in the meta-queue is matched with an independent information element in the independent information element set, and an information element queue to be executed is generated according to the matching result; the rule included in the independent information element in the information element queue to be executed is executed by the rule engine.

In one embodiment, the computer device described above can be a server or a terminal. The server may be an independent physical server or a server cluster composed of multiple physical servers, and the terminal may be a mobile phone, a tablet computer, a personal digital assistant, or a smart device. As shown in Figure 10, A schematic diagram of the internal structure of a computer device in one embodiment. The computer device is applicable to the server 102 in the application environment of FIG. The computer device includes a processor coupled through a system bus, a non-volatile storage medium, an internal memory, and a network interface. The processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device. A non-volatile storage medium of a computer device stores an operating system, a database, and computer readable instructions. The database may store data related to an information element set generation method and a rule engine-based rule execution method provided by the foregoing various embodiments, such as a set of independent information elements. The computer readable instructions are executable by a processor for implementing an information element set generation method and a rule engine based rule execution method provided by the above various embodiments. The internal memory in the computer device provides a cached operating environment for operating systems and computer readable instructions in a non-volatile storage medium. The network interface may be an Ethernet card or a wireless network card, etc., for network connection with an external terminal or server. For example, the computer device can be networked through a network interface with a plurality of terminals 104 in the application environment of FIG.

It will be understood by those skilled in the art that the structure of the computer device shown in FIG. 10 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied. The computer device may include more or fewer components than those shown in the figures, or some components may be combined, or have different component arrangements. For example, the computer device in the figure may also include a display screen or the like.

One of ordinary skill in the art can understand that all or part of the process of implementing the above embodiments can be completed by computer readable instructions, which can be stored in a non-volatile computer. The readable storage medium, which when executed, may include the flow of an embodiment of the methods as described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or the like.

The technical features of the above-described embodiments may be arbitrarily combined. For the sake of brevity of description, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction between the combinations of these technical features, All should be considered as the scope of this manual.

The above described embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed. It is not to be construed as limiting the scope of the invention patent. It should be noted that a number of variations and modifications may be made by those skilled in the art without departing from the spirit and scope of the present application. Therefore, the scope of the invention should be determined by the appended claims.

Claims

An information element set generation method includes:

Obtaining the original information element in each original information element set;

Performing a similarity calculation for each of the two original information elements to generate a corresponding original similarity;

And extracting independent information elements in the plurality of original information elements according to the plurality of original similarities, and generating an independent information element set, where the original similarity of any two independent information elements in the independent information element set is less than a preset similarity threshold.
The method according to claim 1, wherein the performing similarity calculation on each of the two original information elements to generate a corresponding original similarity comprises:

Extracting the original keywords in each original information element;

Obtaining preset keyword weights corresponding to each original keyword;

Generating an original information element vector with each original information element according to a corresponding preset keyword weight of each original information element;

The similarity calculation is performed on the original information element vector corresponding to each of the two original information elements, and the corresponding original similarity is generated.
The method according to claim 2, wherein said extracting original keywords in each of the original information elements comprises:

Each original information element is segmented according to a preset word segmentation algorithm to generate a corresponding plurality of original words; and

The original words in each original information element that match the preset keywords in the preset keyword library are used as original keywords.
The method according to claim 2, wherein the calculating the similarity of the original information element vector corresponding to each of the two original information elements to generate a corresponding original similarity comprises:

First information element vector corresponding to every two original information elements
Second information element vector
According to the formula
Perform similarity calculations to generate corresponding original similarities
Where W 0k is the first information element vector
Corresponding preset keyword weight, W Ak is the second information element vector
The corresponding preset keyword weight.
A rule execution method based on a rule engine, comprising:

Obtaining an independent information element set generated by the information element set generation method according to any one of claims 1 to 4;

Obtaining a message element queue to be matched, where the information element queue to be matched includes a plurality of original information elements;

Matching each original information element in the to-be-matched information element queue with an independent information element in the independent information element set, and generating a to-be-executed information element queue according to the matching result;

The rules included in the independent information element in the to-be-executed information element queue are executed by a rule engine.
The method according to claim 5, wherein the matching each original information element in the queue of information to be matched with the independent information element in the set of independent information elements, and generating a candidate according to the matching result Execute the information element queue, including:

Performing similarity calculation on each original information element in the to-be-matched information element queue and the independent information element in the independent information element set, and generating a corresponding matching similarity;

And the independent information element corresponding to the matching similarity threshold is greater than the independent information element that matches the corresponding original information element; and

And generating, according to the independent information element matched with each original information element, a to-be-executed information element queue corresponding to the to-be-matched information element queue.
An information element set generating device, characterized in that the device comprises:

An original information element obtaining module, configured to acquire an original information element in each original information element set;

a raw similarity generating module, configured to perform similarity calculation on each of two original information elements to generate a corresponding original similarity; and

An independent information element set generating module, configured to extract independent information elements in the plurality of original information elements according to the plurality of original similarities, and generate an independent information element set, where the original two independent information elements are original The similarity is less than the preset similarity threshold.
A rule execution device based on a rule engine, characterized in that the device comprises:

An independent information element set obtaining module, configured to acquire an independent information element set, where the independent information element set is generated according to the information element set generating method according to any one of claims 1 to 4;

a to-be-matched information element queue obtaining module, configured to obtain a to-be-matched information element queue, where the to-be-matched information element queue includes a plurality of original information elements;

The to-be-executed information element queue generating module is configured to match each original information element in the to-be-matched information element queue with an independent information element in the independent information element set, and generate a to-be-executed information element queue according to the matching result; and

And a rule execution module, configured to execute, by using a rule engine, a rule included in the independent information element in the to-be-executed information element queue.
One or more non-transitory readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the following steps:

Obtaining the original information element in each original information element set;

Performing a similarity calculation for each of the two original information elements to generate a corresponding original similarity;

And extracting independent information elements in the plurality of original information elements according to the plurality of original similarities, and generating an independent information element set, where the original similarity of any two independent information elements in the independent information element set is less than a preset similarity threshold.
The storage medium according to claim 9, wherein the step of performing similarity calculation on each of the two original information elements by the processor to generate a corresponding original similarity comprises:

Extracting the original keywords in each original information element;

Obtaining preset keyword weights corresponding to each original keyword;

Generating an original information element vector with each original information element according to a corresponding preset keyword weight of each original information element;

The similarity calculation is performed on the original information element vector corresponding to each of the two original information elements, and the corresponding original similarity is generated.
A storage medium according to claim 10, wherein said processor executes The steps of extracting the original keywords in each of the original information elements, including:

Each original information element is segmented according to a preset word segmentation algorithm to generate a corresponding plurality of original words; and

The original words in each original information element that match the preset keywords in the preset keyword library are used as original keywords.
The storage medium according to claim 10, wherein the performing, by the processor, performing a similarity calculation on the original information element vector corresponding to each two original information elements, and generating a corresponding original similarity, comprises:

First information element vector corresponding to every two original information elements
Second information element vector
According to the formula
Perform similarity calculations to generate corresponding original similarities
Where W 0k is the first information element vector
Corresponding preset keyword weight, W Ak is the second information element vector
The corresponding preset keyword weight.
One or more non-transitory readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the following steps:

Obtaining an independent information element set generated by the information element set generation method according to any one of claims 1 to 4;

Obtaining a message element queue to be matched, where the information element queue to be matched includes a plurality of original information elements;

Matching each original information element in the to-be-matched information element queue with an independent information element in the independent information element set, and generating a to-be-executed information element queue according to the matching result;

The rules included in the independent information element in the to-be-executed information element queue are executed by a rule engine.
The storage medium according to claim 13, wherein each of the original information elements in the queue of information to be matched and the independent information elements in the set of independent information elements are matched by the processor. And generating, according to the matching result, the step of executing the information element queue, including:

Performing similarity calculation on each original information element in the to-be-matched information element queue and the independent information element in the independent information element set, and generating a corresponding matching similarity;

And the independent information element corresponding to the matching similarity threshold is greater than the independent information element that matches the corresponding original information element; and

And generating, according to the independent information element matched with each original information element, a to-be-executed information element queue corresponding to the to-be-matched information element queue.
A computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The following steps:

Obtaining the original information element in each original information element set;

Performing a similarity calculation for each of the two original information elements to generate a corresponding original similarity;

And extracting independent information elements in the plurality of original information elements according to the plurality of original similarities, and generating an independent information element set, where the original similarity of any two independent information elements in the independent information element set is less than a preset similarity threshold.
The computer device according to claim 15, wherein the step of performing similarity calculation on each of the two original information elements by the processor to generate a corresponding original similarity comprises:

Extracting the original keywords in each original information element;

Obtaining preset keyword weights corresponding to each original keyword;

Generating an original information element vector with each original information element according to a corresponding preset keyword weight of each original information element;

The similarity calculation is performed on the original information element vector corresponding to each of the two original information elements, and the corresponding original similarity is generated.
The computer device according to claim 16, wherein the step of extracting the original keyword in each original information element performed by the processor comprises:

Each original information element is segmented according to a preset word segmentation algorithm to generate a corresponding plurality of original words; and

The original words in each original information element that match the preset keywords in the preset keyword library are used as original keywords.
The computer device according to claim 16, wherein the step of performing a similarity calculation on the original information element vector corresponding to each of the two original information elements, and generating a corresponding original similarity, comprising:

First information element vector corresponding to every two original information elements
Second information element vector
According to the formula
Perform similarity calculations to generate corresponding original similarities
Where W 0k is the first information element vector
Corresponding preset keyword weight, W Ak is the second information element vector
The corresponding preset keyword weight.
A computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The following steps:

Obtaining an independent information element set generated by the information element set generation method according to any one of claims 1 to 4;

Obtaining a message element queue to be matched, where the information element queue to be matched includes a plurality of original information elements;

Matching each original information element in the to-be-matched information element queue with an independent information element in the independent information element set, and generating a to-be-executed information element queue according to the matching result;

The rules included in the independent information element in the to-be-executed information element queue are executed by a rule engine.
The computer device according to claim 19, wherein the processor performs matching to match each original information element in the to-be-matched information element queue with an independent information element in the independent information element set. And generating, according to the matching result, the step of executing the information element queue, including:

Performing similarity calculation on each original information element in the to-be-matched information element queue and the independent information element in the independent information element set, and generating a corresponding matching similarity;

And the matching similarity is greater than the independent information element corresponding to the preset similarity threshold, as the phase An independent information element that matches the original information element; and

And generating, according to the independent information element matched with each original information element, a to-be-executed information element queue corresponding to the to-be-matched information element queue.