Mittal et al., 2025 - Google Patents
A neuro-fuzzy algorithm for query expansion and information retrievalMittal et al., 2025
- Document ID
- 3393576611911355715
- Author
- Mittal K
- Vaisla K
- Jain A
- Publication year
- Publication venue
- Multimedia Tools and Applications
External Links
Snippet
Query Expansion (QE) has developed as a critical solution to address the perennial challenges of search accuracy and relevance in the information retrieval domain. In this article, a novel optimized neuro-fuzzy-based QE expansion framework was designed using …
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
- G06F17/30861—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
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30522—Query processing with adaptation to user needs
- G06F17/3053—Query processing with adaptation to user needs using ranking
-
- 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
- G06F17/30675—Query execution
- G06F17/30684—Query execution using natural language analysis
-
- 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
- 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
- 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
- G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
- G06F17/30964—Querying
- G06F17/30967—Query formulation
-
- 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
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- 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
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lytvyn et al. | Methods of building intelligent decision support systems based on adaptive ontology | |
| Deepak et al. | An intelligent inventive system for personalised webpage recommendation based on ontology semantics | |
| Dong et al. | SOF: a semi‐supervised ontology‐learning‐based focused crawler | |
| Tenenboim et al. | Ontology-based classification of news in an electronic newspaper | |
| Alothman et al. | Managing and Retrieving Bilingual Documents Using Artificial Intelligence‐Based Ontological Framework | |
| Khatter et al. | Content curation algorithm on blog posts using hybrid computing | |
| Lim et al. | Knowledge seeker-ontology modelling for information search and management | |
| Singh et al. | Optimal feature selection and invasive weed tunicate swarm algorithm-based hierarchical attention network for text classification | |
| Yin et al. | Integrating information by Kullback–Leibler constraint for text classification | |
| Allahim et al. | Semantic approaches for query expansion: taxonomy, challenges, and future research directions | |
| Samani et al. | The state of the art in developing fuzzy ontologies: A survey | |
| Bouakkaz et al. | Efficiently mining frequent itemsets applied for textual aggregation | |
| CN114741587A (en) | Article recommendation method, device, medium and equipment | |
| Senthilkumar et al. | Collaborative search engine for enhancing personalized user search based on domain knowledge | |
| Srivastava et al. | Redundancy and coverage aware enriched dragonfly-FL single document summarization | |
| Pham et al. | W-Metagraph2Vec: a novel approval of enriched schematic topic-driven heterogeneous information network embedding | |
| Singh et al. | A new customized document categorization scheme using rough membership | |
| Mittal et al. | A neuro-fuzzy algorithm for query expansion and information retrieval | |
| Jiang et al. | Understanding a bag of words by conceptual labeling with prior weights | |
| Vishwakarma et al. | Fine-Tuned BERT Algorithm-Based Automatic Query Expansion for Enhancing Document Retrieval System | |
| Srilakshmi et al. | Stochastic gradient-CAViaR-based deep belief network for text categorization | |
| Xiao et al. | Group feature aggregation for web service recommendations | |
| Hassan et al. | Predictive and evolutive cross-referencing for web textual sources | |
| Rakholiya et al. | MRDFPD: metadata driven RDF based product discovery framework | |
| El Mir et al. | A hybrid learning approach for text classification using natural language processing |