Query Disambiguation Based on Clustering Techniques - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Query Disambiguation Based on Clustering Techniques

Panagiota Kotoula
  • Fonction : Auteur
  • PersonId : 1033566
Christos Makris
  • Fonction : Auteur
  • PersonId : 992346

Résumé

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.
Fichier principal
Vignette du fichier
468652_1_En_13_Chapter.pdf (358.57 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01821297 , version 1 (22-06-2018)

Licence

Paternité

Identifiants

Citer

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⟩
227 Consultations
39 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More