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WO2001067297A1 - Systeme et procede pour effectuer des recherches sur ordinateur - Google Patents

Systeme et procede pour effectuer des recherches sur ordinateur Download PDF

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Publication number
WO2001067297A1
WO2001067297A1 PCT/IL2001/000214 IL0100214W WO0167297A1 WO 2001067297 A1 WO2001067297 A1 WO 2001067297A1 IL 0100214 W IL0100214 W IL 0100214W WO 0167297 A1 WO0167297 A1 WO 0167297A1
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WO
WIPO (PCT)
Prior art keywords
particular user
search
items
user
users
Prior art date
Application number
PCT/IL2001/000214
Other languages
English (en)
Inventor
Paul Kleinberger
Ron Jacobson
Shlomo Bezem
Original Assignee
Tzunami Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tzunami Inc. filed Critical Tzunami Inc.
Priority to US10/220,710 priority Critical patent/US20040128282A1/en
Priority to AU2001241000A priority patent/AU2001241000A1/en
Publication of WO2001067297A1 publication Critical patent/WO2001067297A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation

Definitions

  • This invention relates to methods for computer searching. More particularly, it relates to methods for adapting computer searches to the needs of particular searchers, and for prioritizing the results of computer searches according to the needs of particular searchers. It further relates to methods for generating a display of search results, to facilitate a searcher's understanding of the nature and scope of the information found by his search. It further relates to creating a display of found information convenient for particular searchers, particularly for searchers searching in a foreign language. It further relates to methods for garnering information about users of a search system, or other computer system.
  • search engines attempt to prioritize the results they present.
  • a typical Internet search may report ten thousand, a hundred thousand, or even several million "hits". Since most users are unlikely to actually look at more than the first 20, or 50, or 100 references, search engines try to put first in their lists of found sites those sites which are most likely to interest the user.
  • Another known method is to prioritize search results according to the apparent importance of the searched word within the found document or site.
  • searching the Internet for example, if the searched word is mentioned in the URL of a found site (if for example one searched for "Ford" and found, among others, http://www.Ford.com), then the site is assumed to be highly relevant to the searcher.
  • the word is mentioned numerous times on the site's html page, then it is presumed that that word is centrally important to the site's content (i.e. it was not mentioned accidentally or peripherally), and the site is accordingly given a high priority in the search results.
  • Computer search results are typically displayed in the form of a list of found items such as URLs, with or without a few lines of additional information further describing each item.
  • Lists are not usually an optimal method for presenting search results, as they require the user to inspect each item on the list individually, if he wishes to be sure not to miss relevant found information.
  • search engines such as Yahoo and ODB, which present searchable information to a user in an organized hierarchical manner, or display categories of found information rather than lists of the found objects.
  • search engines such as Yahoo and ODB, which present searchable information to a user in an organized hierarchical manner, or display categories of found information rather than lists of the found objects.
  • Yet such systems have the disadvantage that they are simply displaying the relevant parts of a pre-organized hierarchy. The hierarchies themselves are painstakingly organized 'by hand' by teams of editors and information experts, and do not vary from one user to another nor from one search to another. Simply, the items found in response to a particular search are displayed in their fixed hierarchical context.
  • a second disadvantage is that such a hierarchy is fixed.
  • the organization of major categories, minor categories, further sub-categories of the minor categories, etc. is determined in advance by the editorial staff, and is the same for all users and for all queries.
  • their hierarchical organization of information is likely to be of some use to the "average" user with a general query, it nevertheless may be of limited usefulness to a particular user with a particular or detailed query, and it does not adapt itself to his particular needs.
  • search engines Alta Vista, Northern Lights
  • search engines present, as part of their display of search results, a listing of subject areas that fall within the area of the search. The user is then able to modify his search request by clicking on the sub -categories presented.
  • these displays do not present an actual hierarchy to the user. Categories and sub-categories are not immediately visible in a manner that allows the user to appreciate the nature of the hierarchy as a whole. Neither do such displays provide the user with tools to manipulate the hierarchical display in a manner which facilitates the process by which they ignore irrelevant categories and focus in on categories of interest to them, such as would be the case if the user were able to explore the hierarchy by opening and closing categories as branches of a tree.
  • the methods of these search engines as well are based on the prior organization, by human editors, of the universe of information content as a whole, and the results do not reflect the organizational structure of the information found by any particular search.
  • Kleinberger did contemplate receiving input from the user as part of the process by which the hierarchical display is organized, he did not contemplate the storing of information from or about the user over the course of a number of searches or other interactions with the system, nor the use of such general information from or about the user or the user population in influencing the method of searching, the sources of information, the choice of results presented, nor the method of organization or presenting those results.
  • Prior art does not, to our knowledge, provide such an option.
  • Prior art in this domain does include systems which translate found HTML pages from one language to another, (Alta Vista does this, for example), yet those systems do not facilitate the user's interaction with the display of found information. They aid the user only after he has interacted with the search process, has read (without assistance) the display of found objects, and has selected a site to visit.
  • Another relevant area of prior art concerns methods for tailoring a search process to the needs of a specific user, or to the needs of a specific group of users, or to the needs of a specific type of user.
  • Prior art in this area seems to be limited to collecting and indexing of information on a particular subject or set of subjects.
  • sites on the Internet offer searches on the subject of the game of golf. They index, and provide for searching, a variety of sites whose contents are of interest to users interested in playing golf or watching golf be played.
  • search engines that tailor the search process itself, and the display of search results, to the tastes and abilities of a particular population of users.
  • a young teenager searching for the word "glass" on the Internet will be interested in an entirely different set of URLs from those that would interest a physical chemist or an interior decorator, yet on existing search engines operating according to the principles known to prior art, the teenager, the physical chemist, and the decorator, searching on any given search engine, will receive identical sets of results despite their very different needs.
  • Another relevant area of prior art relates to methods for collecting information about users of a computer system, particularly of a search system.
  • Information about users is useful, whether for tailoring the operation of a system or for other purposes.
  • Information about users, their areas of interest, preferences, tastes, and behaviors, can be of great commercial value.
  • information about users is not easily available. Users are often reluctant to provide such information to commercial Internet sites, and are resistant to allowing such information to be collected about them.
  • Certain methods for collecting user information are of course in common use today on the Internet. The most popular of these is simply to request users to sign up with the site or service, and as part of the sign-up process to request from them certain demographic information.
  • Zip code (indicating part of country, and in some cases type of neighborhood), age, type of occupation, and level of income are typical questions in this context. Other information can be gleaned from analysis of other details supplied by the user. His email address and/or IP address, for example, can often provide clues as to his location and (by implication) language preferences. This information is then typically used to control the selection of banner advertising to which the user is exposed. In the case of search engines, a combination of such demographic information on the one hand, and the user's current search request on the other, are often used in combination to select what is considered the most appropriate banner ad to present to him. A user searching for "notebook” is likely to find a banner ad from one of the notebook computer manufacturers accompanying his search results. If his IP address ends in ".fr", he is also likely to see the banner ad in French.
  • This invention relates to methods for computer searching. More particularly, it relates to modifying procedures of computer searching and procedures for prioritizing the results of computer searches, using stored information known to the system about the searchers, so as to enhance the usefulness of the results to the searchers. It further relates to methods for automatically generating a hierarchical display of search results, and for adapting that display based on known information about the searcher. It further relates to translating search output for the convenience of searchers. It further relates to methods for garnering information about users based on their activities when using a computer search system or other computer system.
  • the present invention improves on prior art computer search and Internet search procedures, which improvements make it easier for a searcher to find what he needs.
  • the embodiments described below constitute system and method for organizing the results of a search so that the searcher can easily ignore all the sites that are clearly irrelevant, and so that he can clearly see the found information in categories.
  • Stored information about the user both demographic information and information gleaned from his previous interactions with the search engine, is used to determine what kinds of information, and what methods of presenting information, are most likely to be of use to the searcher. Then, the search process and presentation of search results are tailored accordingly.
  • a search process using these methods is more likely than a conventional search engine to provide the user with what he needs, and to provide it in a format that is easy for him to use.
  • the present invention overcomes the limitations of prior art by providing a method whereby items found by a search are presented to each particular user in a priority order which reflects that user's needs and tastes and characteristics.
  • the use of such a system can greatly facilitate computer searching in many contexts. Consequently, one object of this invention is to use information known to the system about the searcher to influence the choice of sites presented in the reporting of the results of an Internet search, and similarly to use information known to the system about the searcher to influence the prioritization of the sites presented.
  • the present invention further overcomes limitations of prior art by providing system and method for presenting items found by computer searching in an organized hierarchical display, the hierarchy being calculated based only on the found information and not based on a pre-existing hierarchy of subjects known in advance to the system.
  • Such a system can be useful in many contexts, and greatly facilitates searching of the Internet and other computerized contexts.
  • the present invention further overcomes limitations of prior art by providing system and method for interfacing with existing search engines, and overcoming the limitations of those engines by organizing the results they present, prioritizing according to known stored characteristics of a searcher, and also by presenting the items found by those search engines in a organized hierarchical display, although neither information about a prioritization for a particular user nor appropriate hierarchical information is provided by the output of the search engines themselves.
  • a search system that presents search results in an organized hierarchical manner facilitates the user's understanding of what has been found.
  • a further object of the present invention is to translate the search requests of a user before transmitting them to a search engine, and to translate the results of a computer search before presenting them to a user.
  • the present invention further overcomes limitations of prior art in that prior art, although it does contemplate translating documents and Internet web sites, yet it does not include tools which substantially facilitate the search process for users searching material in a foreign language.
  • a further object of the present invention is to provide means for specializing search engines for particular populations of users.
  • a further object is to provide non-intrusive methods for collection information about users.
  • the invention constitutes an advance over prior art in that it contemplates using information gleaned from users of a computer system to tailor the output of the system to the user's needs, thereby overcoming user resistance to the collection of such information.
  • the invention further comprises methods for collecting useful information about the user unobtrusively, without interrupting his chosen voluntary activities, and without requiring of him special activities such as answering questions. Definitions:
  • Internet reference is made herein to the Internet, to Internet searching, etc.
  • the inventions described below as well as the descriptions of prior art are equally applicable to searching on intranets, extranets, and on large and small networks and on individual computer systems.
  • our disclosure and the examples of use given herein are sometimes described in terms of Internet searching, this is to be understood to be an example of the use and utility of the inventions, and is not intended to imply any limitation in the scope of their use.
  • the inventions here disclosed should be understood to be applicable as well to such systems as intranets, WANs, LANs, and to individual computer systems.
  • “Text”, "Site”, “URL” the words “text” and “site” or “sites” and “URL” or “URLs” are sometimes used herein to refer to the object found by a search. It is to be understood that these words when used in this context are used by way of example, and that the found objects may be text documents, Internet sites, or any other unit of found information existing in a computer system, LAN, WAN, Extranet, Intranet or the Internet, and described or describable by words. In particular, it includes web pages, graphics objects, multimedia objects, etc.
  • Preference The disclosure herein states in various contexts that priority or preference is give for certain selections over other selections, or for certain arrangements over other arrangements, because they have some characteristic which the user, or some group of users, has been shown to prefer or can reasonably be assumed to prefer.
  • This concept of user preference should be taken to include also the opposite phenomenon, namely negative preference (low priority, exclusion) given to certain selections or arrangements because they have some characteristic which the user or group of users has been show not to prefer, or could reasonably be assumed not to prefer. Since it would be tedious to repeat both the positive and the negative side of this "preference” in every context, we here state that when the positive preference is referred to in the following, the possibility of the use of "negative preference” (low priority, exclusion) should be understood to be meant as well.
  • Similar in the following disclosure, when two users are said to be “similar”, this means that there exists a positive correlation among data elements associated with the two users, from at least some subset of the data associated with the two users within the system.
  • a group of users is said to be similar to a given user, this means that there exists a subset of the set of all users of the system, each member of the subset is similar to the user, over at least some subset of the data know to the system about the users.
  • Display the word “display”, used herein to describe the process of making visible, to one or more users, the results of some process of computer searching or computer analysis.
  • the word “display” should be understood to include not only such traditional forms of display as showing the results on a computer monitor such as a CRT monitor or LCD monitor, but also any other method or mechanism of making the results so visible, including processes of printing the results, and processes by which the results are transmitted to systems capable of making them visible to users, either immediately or subsequently.
  • FIG. 1 is method for displaying prioritized results of a computer search, according to the present invention
  • FIG. 2 is a system for displaying prioritized results of a computer search, according to the present invention
  • FIG. 3 is a method for choosing search engines for executing a computer search, according to the present invention
  • FIG. 4 is a method for analyzing and displaying the results of a computer search, according to the present invention.
  • FIG. 5 is an example of output generated by an embodiment of the present invention.
  • FIG. 6 is a further example of output generated by an embodiment of the present invention.
  • FIG. 7 is a further example of output generated by an embodiment of the present invention.
  • FIG. 8 is a further example of output generated by an embodiment of the present invention.
  • FIG. 9 is a method for facilitating computer searching in foreign languages, according to the present invention.
  • FIG. 10 is a method for selecting among alternative possible translations of words, according to the present invention.
  • Figure 1 describes the procedural steps of a method for enhancing the output of computer search process or other item selection process.
  • the system receives a data set, a collection of items from a data set source.
  • a data set source will typically be a standard search engine, to which a user has supplied a query.
  • the system prioritizes the items according to information know to it about the user's preferences.
  • the system may eliminate from the data set items with a low priority, i.e. items which seem unlikely to be of interest to the user according to the calculations of step 2.
  • items of the data set are displayed on a display device or printed on a printing device.
  • step 4 includes displaying the results in a manner which gives expression to the prioritized ranking of the items according to the results of step 2.
  • Figure 2 presents a computer system for implementing the method described in Figure 1.
  • User input 10 is provided by a user to a data set source 12, such as an Internet search engine.
  • Data set source 12 provides (through computer searching or by some other means) a data set, and passes the data set to data set organizer 14.
  • Data set organizer 14 refers to characteristics of items in the data set, and also to stored information about the user, or stored information about other users similar to the user, from user information data storage 16, and calculates priority scores for the items in the data set. Data set organizer 14 may also eliminate items from the data set because of low priority scores.
  • the prioritized items are then passed to display system 18, which then displays them so that they can be seen by a user.
  • the method of display gives expression to the relative priority scores of the various items.
  • information stored on a computer system about the searcher is used to influence the prioritization of the sites presented to the user on a display.
  • low priority sites may be eliminated from the display.
  • the subset of found sites reported to the user is may be ordered, and may be selected, according to one or both of the following methods:
  • Priority is given to items having characteristics known to characterize items suitable to a particular user.
  • Priority is given to items having characteristics known to characterize items suitable to users who are similar to a particular user.
  • Measures of similarity which might be relevant to users viewing Internet sites, for example, might include: similarity in demographic information (for example geographical area, age, profession), similarity in opinions expressed when evaluating Internet sites or other items (for example in evaluating sites found by searches), and similarity in behavior or performance while using the site or while using software downloaded from the site (for example similarity in the speed with which users respond to particular stimuli presented by the site).
  • characteristics of the sites may be indicated by the sites themselves (e.g. in meta-tags), or deduced about the site from some known characteristics generally found to characterize sites consistently (e.g. site pages referring to themselves as "home" pages and including hyperlinks referring to offers of employment are generally owned by commercial entities). Yet the characteristics of the site relevant to its appropriateness for selection need not be limited to those which can be characterized a priori; it is sufficient to have observed a statistical correlation between any measurable characteristic of a site and any of the expressions of opinion or preference mentioned above.
  • information known to the system about a particular user is used to influence the method of performing the Internet search.
  • Information about the user and his preferences, or information about users known to be similar to the particular user in some respect, and their preferences, may be used to influence or control the execution of the search itself, in a manner similar to that described above for controlling the prioritizing of sites found by the search.
  • a meta-search engine an engine which sends a search request to several independent search engines and presents to the user the combined results interpret the search request sufficiently to determine which particular search engines are most likely to provide good information for the given subject, and re-direct the users query to such sites.
  • Our invention goes beyond this basic idea, however, and contemplates modifying the choice of search engines according to the personal characteristics and known preferences of the particular user, and/or of a set of users similar to the particular user.
  • the engine might recognize that a particular query is concerned with matters of health, it might direct the search to one set of sources of information if the query comes from a mother and housewife, and quite another set of sources of information if the query comes from a medical specialist.
  • Step 20 is the receiving of a search request from a user.
  • Step 22 involves identifying candidate search engines, those known to have access to indexes that include information relevant to the searched objects.
  • the characteristics of the candidate search engines are compared to a set of characteristics of search engines deemed desirable for a particular user.
  • at least one search engine is selected from among the candidate search engines according to the calculations of step 24, and at step 28, the search is executed using the selected search engine or search engines.
  • the functional correlations which control the behavior of the search engine may be linked directly to opinions expressed by the user. For example, he may consistently approve of one kind of site, or tend to use information that comes from one kind of site, and consistently tend to ignore pointers to sites of another kind. Alternatively, they may be linked to the user indirectly, through the correlations between this user and other users with whom he is similar in some respect. For example, we might not know what kind of site he likes when asking about cars, yet know what kind of site he likes when asking about sports; if we also know what kind of sites about cars are preferred by other users who share his taste in sites about sports, we can use that information to choose what to present to this user.
  • An additional embodiment of the present invention involves the presenting of the results of a computer search in hierarchical format, where the hierarchy of texts is constructed from the results of a particular search executed by a particular user, and is not the result of a hierarchical structure which was determined in advance of the particular search.
  • the hierarchy is constructed in such a manner that the material found is divided into major categories, each major category may be divided into several subcategories, each subcategory may be further divided into sub-sub-categories, and so on.
  • the level of detail that can be achieved depends only on the desires of the user and the amount of material available to be presented.
  • Figure 4 presents a method for accomplishing this, according to the present invention.
  • a first input data set of items is established.
  • this first input data set of items will be a set of items supplied by a search engine in response to a user's search request, yet alternatively the first input data set of items may be any set of items characterized by keywords or descriptions of any sort, or capable of being so characterized, and may be items received from one search engine, from a plurality of search engines, or from any other source.
  • a characteristic common to a plurality of items from among the items of the input data set is found.
  • the analysis is performed by treating the descriptions of the found items provided by the search engine (e.g. the text accompanying each URL in a typical Internet search engine results list) as keywords or descriptors of the found objects, and analyzing them statistically to identify keywords or descriptors common to a relatively large sets of items.
  • Other techniques of analysis may be applied, so long as the result is to identify a characteristic common to a plurality of items from among the items of the data set.
  • the set of the items of the input data set that have the characteristic in common is called the "selected” set, and the input data set from which it was selected is called the selected set's "including” set.
  • the set of the items consisting of all items of the including set exclusive of the items belong to the selected set is called the "unselected” set. (This set consists of the items of the input data set that do not have the designated characteristic common to the items of the selected set.)
  • the unselected set has the same "including set” as does the selected set.
  • the name of the characteristic common to the selected set, or some graphical or other representation of that characteristic is displayed on a display device.
  • the selected set is taken to be a new input data set, and the process is set to repeat from step 42, where a new characteristic common to a new selected set is identified.
  • the name or representation of the characteristic common to the new selected set is displayed in a manner which shows it to be associated with, and possibly subordinate to, the name or representation of the characteristic of the selected set's including set. Note that both a selected set and an unselected set are wholly contained subsets of their including sets.
  • the unselected set may also be treated as a new input data set, and the process may be further continued by repeating from step 42.
  • Increasingly detailed analyses of selected and of unselected sets may be repeatedly undertake to any desired degree of detail, or until the sets in question cannot be further subdivided in the manner described.
  • Figures 5-8 are examples of the output from such a process, according to a preferred embodiment.
  • the examples were generated by passing a search request ("London") to an Internet search engine (www.Google.com), receiving Google's standard output (in this case 218 found URLs), treating the text accompanying the URL designation in Google's output as a set of descriptors for each URL, ignoring common words ("and", "the”, etc.), and then subjecting the resulting data set to the method of analysis and display described in Figure 4.
  • Figure 5 shows a first set of results.
  • Application of step 40, step 42, and step 44 to the initial data set produced the word "London”: 202 URLs were found to have the word "London” as part of their descriptions, hence were selected into the selected set at that point.
  • Application of step 48 to the unselected set (the set of URLs which did not include the word “London") produced the word "texts", found in the descriptions of 10 of the remaining URLs.
  • An additional application of step 48 to the remaining unselected set determined that three of the remaining URL descriptions included the word pair "search engine", two had the word "internet” in common, and one URL was found to have no characteristics in common with any of the previously selected URLs.
  • Figure 6 shows the result of further application of steps 46 and 48 to the data set.
  • step 46 to the first selected set (the set selected by the presence of the word “London”), caused the selection of a set characterized by the word “theatre".
  • 116 URLs of those with the word “London” common to their descriptions, also had the common word “theatre”.
  • step 48 repeated application of step 48 to the unselected sets at that point produced the list of words following "theatre" in the figure. For example, from within the set selected by the word “London” but unselected by the word theatre, 20 were selected by the word “recreation”. Of those selected by "London” but unselected by “theatre” and further unselected by “recreation", 12 were selected by the word "guide”. Further application of the same principles produced the further characterizations "business", “sport”, and so on.
  • FIGS 7 and 8 represent the result of continuing the process described herein, on the same data set, to increasing levels of detail.
  • the display was organized by placing words describing selected sets below and to the right of words describing those selected set's including sets. Unselected sets having a common including set are listed one under another at the same level of indentation. Thus, “theatre”, “recreation”, “guide”, etc., are listed at a same level of indentation, under "London”.
  • one advantage of the method herein described is that the choice of major and minor categories displayed to the user is determined uniquely by the particular set of results presented to the display module by the external search engine. The process does not need to refer, nor does it refer, to any prior knowledge about the subject not to any particular structure or relationship of subjects or categories know or determined in advance of the search.
  • a software implementation of the method of Figure 4, demonstrated by example in Figures 5-8, is a client-server system in which the user interacts with the client software and makes a search request. That request is sent to the server system which sends it out to a selected group of Internet search engines, receives the results supplied by those engines, and extracts from them the textual material describing the set of sites (URLs) found by those engines. It then organizes that information 'on the fly' into a hierarchical information structure. It does this by analyzing the textual material to find the most important common subjects existing among the found data, and identifying them as major categories. It then repeats the process recursively on each identified major category to produce further sub-categories and sub-sub-categories, to any desired level of detail.
  • FIG. 5 shows an example of the display provided by the client software at that point.
  • Figures 6 through 8 further demonstrate the fact that the process by which iterations of the loop described in Figure 4, where either step 46 or step 48 leads to a reiteration of step 42 in a recursive process, may be influenced or controlled by a user in an ongoing interaction. According to this process, a user, responding to a display, clicks on categories of information that interest him, thereby commanding further iterations of the process described by Figure 4, and thereby "drills down" into the hierarchy, getting at each stage increasingly detailed divisions and subdivisions of the chosen subject, according to the methods presented herein.
  • this hierarchy may be done automatically, based on available information about the found sites, and requires no human intervention.
  • the hierarchy is not fixed in advance - the hierarchy reflects the intrinsic organization of the particular data set of items to be presented. Thus for example in one search "cars" might be a subset of "racing", and in another search “racing” might be a subset of "cars” - the choice would depend on what particular set of internet sites was found, and that would depend in turn on the particular search request, and perhaps depend as well (as hereinabove) on characteristics of the particular user as well. There are two major advantages of this method of displaying search results over the traditional method of presenting a list of sites found.
  • this method presents a "birds' eye” view of the found information. That is, the hierarchy, derived from the set of found items, teaches the user something about the nature and 'landscape' of the information uncovered by his query. In other words, the hierarchy itself constitutes a form of information.
  • this method of displaying the results provides an excellent tool for discarding or ignoring irrelevant sites. It may not be easy, and is sometimes not even possible for a user to specify exactly what he wants, but it usually is quite easy for him to recognize (once presented with a display such as that of Figure 5) what he does not want. Given a display of the sort shown in Figures 5-8, the user easily concentrates his attention on categories that attract him, and never needs to look at any detailed information about sites from categories that clearly do not interest him.
  • step 42 of Figure 4 (the process of choosing and of naming the characteristics which form the basis for selected the selected sets) is influenced by the user's tastes and preferences, or by the tastes and preferences of a group of users know to be similar to the him in some respect.
  • Users' tastes and preferences may have been expressed explicitly, or implicitly.
  • An example of an explicitly expressed preference is that a user requests that e.g. nouns appearing in the descriptions of items be used as defining characteristics, but adjectives not be so used.
  • An additional example is that a user asks that certain tests be applied to items of the data set and the results used as defining characteristics, for example by requesting that the display of Internet search results distinguish between commercial sites and noncommercial sites.
  • Examples of implicitly expressed tastes and preferences include situations where the user, without making any general statement about his preferences, asks the system to hide or ignore defining characteristics, and the characteristics he chooses to be hidden and ignored are frequently adjectives and never nouns, or similarly, where a given user frequently and typically investigates found Internet sites whose URLs end in ".com”, and never visits sites whose descriptions include the word "my”, as in "here's what I did with my vacation", or "here is a picture of my favorite car”).
  • user preferences controlling the construction of a hierarchy the situation is similar to those we've seen above with respect to the choice of search engines and the choice of found sites to be presented to the user.
  • the preferences which control or influence the choice of categories may be those of the user himself, or those of a sub-set of the set of users of the system, which subset has expressed opinions or engaged in behaviors which correlate positively with the particular user's opinions and behaviors.
  • the sub-set of users whose preferences control the process might be a sub-set to which the particular user belongs by virtue of similarity of demographic details of one sort or another.
  • Examples of areas in which the expressed or implied preferences of the particular user, or of users similar to the particular user, can be used with good effect in influencing or controlling the selection of major and minor categories for organization and display of the search results include
  • the overall effect of the use of the techniques described above is to provide a search engine capable of adapting itself to particular users, and able to do so painlessly and automatically.
  • the search process, the choice of found sites to display, and the method of presentation of that display, all can be molded to the particular user. His opinions and behaviors can be matched with the opinions and behaviors of other users to identify those who are similar to him in certain respects, and then their opinions and behaviors can be used to further modify the search experience in ways likely to suit the particular user's needs.
  • the presentation of the results of the Internet search in the form of a spontaneously generated hierarchical structure not dependant on previous human organization in itself constitutes a major facilitation of the search process, whether or not the hierarchy is influenced by being adapted to the specific user's tastes, opinions, and behaviors, and to those of users similar to him.
  • search results can be further enhanced using information about user preferences and user characteristics known to the system, is for the search results to be translated before being presented to the user.
  • Figure 9 presents a method for accomplishing this purpose.
  • This embodiment further adapts the search process to the need of an individual searcher by optionally translating his search request into a target language, and by translating into his language the display of search results.
  • Search engines generally respond to a search request by presenting the users with a summary (usually in the form of an annotated list) of what was found, allowing the users to select elements from the list for closer inspection. If the summary is in a language convenient to them, users can more easily peruse the body of found information and choose items that seem to justify the effort to read them in the original language. Automatic machine translation is not yet highly perfected, but for the purpose described here, the levels of automatic translation available in current commercialized software packages is likely to be sufficient.
  • search engine summary texts are generally based on keywords from the found sites themselves and/or quotes (sometimes fairly arbitrary) from the text of the found site, the 'literary' level of the texts presented (elegance of the language, consistency, even completeness of sentences) is usually not high, consequently the demands on a translation system to produce elegant, consistent, and complete output is correspondingly reduced.
  • Figure 9 presents a method for facilitating searching for a user wishing to search material in a language not his own.
  • the method involves the following steps.
  • a search request is received from a user who makes his request in his native language.
  • that request is translated into the language or languages of the material he desires to search.
  • his search request in the language of the material to be searched, is submitted to processing by one or more search engines.
  • a list of found items is received from the search engine(s).
  • a hierarchical arrangement of the search results may be prepared, according to the principles described herein and in particular in connection with the discussion of Figure 4.
  • the search results (whether transformed into a hierarchy by step 58 or in their original form) are translated into the user's language, and displayed to him.
  • the hierarchical display created through the use of the methods described by Figure 4 can be produced in the form of a hierarchical "tree" of results, a hierarchical structure in which "branches" (category names) are typically labeled by a single word (the name of the category), or by several words which happen to all characterize a group of items but which have no necessary syntactical relationship (e.g. "modem connect baud"), or by a short phrase of words typically found together (e.g. "baud rate,” "life insurance”).
  • Figure 10 presents this method in further detail.
  • the system receives a word to be translated.
  • a dictionary lookup is performed to see if there exists more than one possible translation of the word. If not, then if any translation exists, the word is translated at step 74. If more than one candidate translation exists, then at step 76, a "first list" of words frequently associated with each of the candidate translations is identified. (This process, of course, may be done in advance for all the words of the dictionary).
  • the context in which the word to be translated appears is inspected, to create a "second list" of words appearing with it in the current context.
  • the second list might optionally include the words appearing near the word to be translated in all of the places where the word to be translated appears within the initial input data set, or in near the occurrences of the word to translated within the selected set, as described above.
  • step 80 a comparison is made between the meanings of the words found in step 78, and the meanings of the words found to be associated with each of the candidate translation words in step 76. In most cases, one and only one of the candidate translations will be found to be associated with a set of words whose meanings have much in common with the meanings of the words found in step 78.
  • One method of implementing the comparison is to translate all the words of one of the lists (or all the words for which an unambiguous translation is known) into the language of the other list, and then simply comparing the translated words of the one list to the words of the other list. This might be done in either direction (i.e. translating the first list, or translating the second list), or even in both directions.
  • Such a search engine might have some or all of the following characteristics: • Limitation of found material: material considered not appropriate for children would simply not appear among the output of the search engine. This is to be contrasted with the current state of the art, in which software intended to prevent children's exposure to objectionable material will usually prevent the child from loading a URL containing objectionable material, but will not prevent references to such sites from appearing in response to search requests. (In some cases, if sufficient 'offensive' material is presented in the sites' descriptions as they appear in the search output, then all the search output, (offensive and inoffensive) may be prevented from display by the same protective software.)
  • the search engine designed for children contemplated in this embodiment would move the selection of acceptable vs. objectionable material into the search process itself. That is, either the search would be based on an index of sites pre- filtered to eliminate objectionable material from the entire index, or else at the time of the search, the search engine having identified the searcher as a child, would filter the results of the search and present only appropriate found information to the searcher.
  • a school child could search for "Little Women" and not risk finding a list of porno sites.
  • search engines specialized for children can in fact be generalized to the idea of search engines specialized for any particular target population with common characteristics. For example, there exists a population of adult users who are different from children in that they are indeed adults, but somewhat similar to children in that they are (self-declared) unsophisticated in the ways of the Internet, electronic searching, and hi-tech in general. Such users could similarly benefit from a search engine which translated naive searches into language more likely to find the required information, then translated the search results back into categories likely to be understood, accompanied by explanations, or hints for how to search further in the particular subjects, etc.
  • hi-tech users are relatively unlikely to be interested in home pages created by the world's high school student population, and doctors searching for information about the known characteristics of pharmaceutical products would be unlikely to want to read anecdotes from patients comparing notes in a newsgroup context.
  • a general-purpose search engine could tailor its output to a particular population or group.
  • the searching process itself, and indeed the indexing process on which the search results are based are more finely honed than would otherwise be possible, because the search engine is specialized with the needs of a particular population in mind.
  • the purchaser of the software and the user of the software may not have identical interests. It may be useful to specialize search software according to the needs of, say, an educational context or a corporate context, and have the engines behavior reflect the priorities of the purchaser of the software, which are not necessarily identical to that of the users.
  • a "commercial" search engine might be considered useful in the corporate environment if it limited the found information to that considered relevant, by the corporation, to furthering the corporation's goals. Thus a given corporation might favor a search engine which did not find information about sex or sports, considering that these are subjects better pursued by the corporation's employees on their own time.
  • Another embodiment of this invention is concerned with methods for collecting information about users, on which the response of the search engine to a search request may be based.
  • information about users, their areas of interest, preferences, tastes, and behaviors is used in various embodiments described herein, and can be of great commercial value in various other ways, yet many users have a great reluctance to providing such information to commercial internet sites, and to allowing such information to be collected about them.
  • the current embodiment of our invention involves several improvements on the methods for collecting such information commonly in use.
  • the first is simply to provide for the collection of cumulative information about users' needs and interests by requiring users to identify themselves to the system before searching. (The identification required is not a 'absolute' identification: the search engine does not in fact need to know the user's actual identity. It is sufficient for the user to identify himself with an alias, so long as he uses the same alias every time he searches.)
  • Another such type of service is to allow users of the search site to store found information on the search server. This can be expanded to allow for users' storing of other sorts of information. It can further be expanded by providing follow-up services relating to previous searches by the same user, for example the automatic reporting of new sites which have recently appeared on the Internet and which answer to search requests the user previously executed.
  • the system is then in a position to accumulate information about him in a 'user profile'.
  • a second source is to record in a database the searches conducted by the user.
  • user's acquiescence to such an operation will best be gained by providing a service, unobtainable and unperformable otherwise, based on the information, such as the 'updated search' mentioned above.
  • a third method is to accumulate information about the user's responses to the search output.
  • a general search produces tens or hundreds of URLs, the users more specific interests and tastes are indicated by his choice of which of the tens or hundreds of URLs to visit.
  • a fourth method is somewhat more subtle: it consists of collecting information on the user based not on the information content expressed by search requests and search choices, but rather based on his behavior when responding to the system.
  • a user responding interactively with a site provides myriad opportunities for observing his tastes and preferences, based not on what he says about himself, but on what he does.
  • behavioral information collected in this manner can be used for other purposes.
  • use of behavioral information to predict both the style and the content of advertising material that might be effective when presented to the specific user.
  • the use of behavioral information to predict both the style and the content of advertising material that might be effective when presented to the specific user.
  • the previous use of the information was characterized as being "to the user's benefit", it is not necessarily the case that the use described here is at the user's expense or to his detriment.
  • a reality in which the user is using a search site and being exposed to advertising thereon it stands to reason that most users would prefer to see ads which might actually interest them, over ads which do not.
  • the system can collect and use the information of the user profile without necessary human intervention, and without dependence on hypotheses of the sort mentioned above (such as the hypothesis that a user with fast and sporty mouse movements is more likely to purchase a fast and sporty car).
  • hypotheses of the sort mentioned above such as the hypothesis that a user with fast and sporty mouse movements is more likely to purchase a fast and sporty car.
  • a particular user's behavioral reactions to a variety of stimuli can be collected and made the subject of statistical analysis, it is possible to determine useful correlations among behaviors without needing to formulate any hypotheses at all.

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Abstract

L'invention concerne un procédé pour effectuer des recherches sur ordinateur. Ce procédé consiste à recevoir un groupe de données initiales à partir d'une source (1) de groupes de données; à classer par priorité des éléments desdites données en fonction des préférences (2) de l'utilisateur, à supprimer de la sélection les éléments de données ayant une priorité basse (3) et à afficher les résultats (4).
PCT/IL2001/000214 2000-03-07 2001-03-07 Systeme et procede pour effectuer des recherches sur ordinateur WO2001067297A1 (fr)

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