Skip to Main content Skip to Navigation
Conference papers

Query Disambiguation Based on Clustering Techniques

Abstract : In this paper, we describe a novel framework for improving information retrieval results. At first, relevant documents are organized in clusters utilizing the containment metric along with language modeling tools. Then the final ranked list (ascending/descending order) of the documents that will be returned to the user for the specific query, is produced. To achieve that, firstly we extract the scores between the clusters and the query representations and then we combine the internal rankings of the documents inside the clusters using these scores as weighting factor. The method employed is based in the exploitation of the inter-documents similarities (lexical and/or semantics) after a sophisticated preprocessing. The experimental evaluation demonstrates that the proposed algorithm has the potential to improve the quality of the retrieved results.
Document type :
Conference papers
Complete list of metadata

Cited literature [27 references]  Display  Hide  Download

https://hal.inria.fr/hal-01821297
Contributor : Hal Ifip <>
Submitted on : Friday, June 22, 2018 - 2:12:47 PM
Last modification on : Friday, June 22, 2018 - 2:24:17 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 6:40:35 PM

File

468652_1_En_13_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Panagiota Kotoula, Christos Makris. Query Disambiguation Based on Clustering Techniques. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.133-145, ⟨10.1007/978-3-319-92016-0_13⟩. ⟨hal-01821297⟩

Share

Metrics

Record views

301

Files downloads

1