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The Effective Relevance Link between a Document and a Query
- Source :
- Database and Expert Systems Applications-Proceedings of the 23rd International Conference (DEXA), Part I, DEXA 2012-International Conference on Database and Expert Systems Applications, DEXA 2012-International Conference on Database and Expert Systems Applications, Sep 2011, Vienna, Austria. pp.206-218, ⟨10.1007/978-3-642-32600-4_16⟩, Lecture Notes in Computer Science ISBN: 9783642325991, DEXA (1)
- Publication Year :
- 2011
- Publisher :
- HAL CCSD, 2011.
-
Abstract
- Session 3A: Personalization, Preferences, and Ranking; International audience; This paper proposes to understand the retrieval process of relevant documents against a query as a two-stage process: at first an identification of the reason why a document is relevant to a query that we called the Effective Relevance Link, and second the valuation of this link, known as the Relevance Status Value (RSV). We present a formal definition of this semantic link between d and q. In addition, we clarify how an existing IR model, like Vector Space model, could be used for realizing and integrating this formal notion to build new effective IR methods. Our proposal is validated against three corpuses and using three types of indexing terms. The experimental results showed that the effective link between d and q is very important and should be more taken into consideration when setting up an Information Retrieval (IR) Model or System. Finally, our work shows that taking into account this effective link in a more explicit and direct way into existing IR models does improve their retrieval performance.
- Subjects :
- Web search query
Information retrieval
Computer science
Search engine indexing
02 engineering and technology
Query optimization
Query language
Ranking (information retrieval)
Query expansion
Web query classification
020204 information systems
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]
0202 electrical engineering, electronic engineering, information engineering
Vector space model
020201 artificial intelligence & image processing
Sargable
Language model
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-642-32599-1
- ISBNs :
- 9783642325991
- Database :
- OpenAIRE
- Journal :
- Database and Expert Systems Applications-Proceedings of the 23rd International Conference (DEXA), Part I, DEXA 2012-International Conference on Database and Expert Systems Applications, DEXA 2012-International Conference on Database and Expert Systems Applications, Sep 2011, Vienna, Austria. pp.206-218, ⟨10.1007/978-3-642-32600-4_16⟩, Lecture Notes in Computer Science ISBN: 9783642325991, DEXA (1)
- Accession number :
- edsair.doi.dedup.....511c396c3380e83ef7ac6b2b27f5aeb3
- Full Text :
- https://doi.org/10.1007/978-3-642-32600-4_16⟩