Hu et al., 2009 - Google Patents
Context-aware online commercial intention detectionHu et al., 2009
View PDF- Document ID
- 14002131059935177630
- Author
- Hu D
- Shen D
- Sun J
- Yang Q
- Chen Z
- Publication year
- Publication venue
- Asian Conference on Machine Learning
External Links
Snippet
With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual transactions happen. For many Web users, their online commercial activities start from …
- 238000001514 detection method 0 title abstract description 29
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/3066—Query translation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/30707—Clustering or classification into predefined classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Alharbi et al. | Evaluation of sentiment analysis via word embedding and RNN variants for Amazon online reviews | |
| Subhashini et al. | Mining and classifying customer reviews: a survey | |
| Xin et al. | The implementation of an AI-driven advertising push system based on a NLP algorithm | |
| Broder et al. | Search advertising using web relevance feedback | |
| Xie et al. | Community-aware user profile enrichment in folksonomy | |
| US8782037B1 (en) | System and method for mark-up language document rank analysis | |
| US8713017B2 (en) | Summarization of short comments | |
| WO2019085236A1 (en) | Search intention recognition method and apparatus, and electronic device and readable storage medium | |
| Tajbakhsh et al. | Semantic knowledge LDA with topic vector for recommending hashtags: Twitter use case | |
| Dong et al. | Ontology-learning-based focused crawling for online service advertising information discovery and classification | |
| Anoop et al. | A topic modeling guided approach for semantic knowledge discovery in e-commerce | |
| Sulthana et al. | Context based classification of Reviews using association rule mining, fuzzy logics and ontology | |
| Khan et al. | A review on sentiment analysis of twitter data using machine learning techniques | |
| Prakash et al. | Lexicon Based Sentiment Analysis (LBSA) to Improve the Accuracy of Acronyms, Emoticons, and Contextual Words | |
| Dadhich et al. | Social & juristic challenges of AI for opinion mining approaches on Amazon & flipkart product reviews using machine learning algorithms | |
| Singh et al. | Deep learning based online fake review detection technique | |
| Chen et al. | Tag-extended collaborative filtering recommendation algorithm | |
| Hu et al. | Context-aware online commercial intention detection | |
| Narmadha et al. | A survey on online tweet segmentation for linguistic features | |
| Chen | BiLSTM-enhanced legal text extraction model using fuzzy logic and metaphor recognition | |
| Huang et al. | Review of intelligent microblog short text processing | |
| Agrawal et al. | An efficient multiple-word embedding-based cross-domain feature extraction and aspect sentiment classification | |
| Mamatha et al. | Supervised aspect category detection of co-occurrence data using conditional random fields | |
| Elmokhtar et al. | Enhanced sentiment classification of phone brands on Twitter with a modified walrus optimizer and novel ensemble method | |
| Kannout et al. | Toward recommender systems scalability and efficacy |