OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

DSRIM: A Deep Neural Information Retrieval Model Enhanced by a Knowledge Resource Driven Representation of Documents

Nguyen, Gia Hung and Soulier, Laure and Tamine-Lechani, Lynda and Bricon-Souf, Nathalie DSRIM: A Deep Neural Information Retrieval Model Enhanced by a Knowledge Resource Driven Representation of Documents. (2017) In: International Conference on the Theory of Information Retrieval (ICTIR 2017), 1 October 2017 - 4 October 2017 (Amsterdam, Netherlands).

[img] (Document in English)

PDF (Author's version) - Depositor and staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
413kB

Official URL: http://doi.org/10.1145/3121050.3121063

Abstract

The state-of-the-art solutions to the vocabulary mismatch in information retrieval (IR) mainly aim at leveraging either the relational semantics provided by external resources or the distributional semantics, recently investigated by deep neural approaches. Guided by the intuition that the relational semantics might improve the effectiveness of deep neural approaches, we propose the Deep Semantic Resource Inference Model (DSRIM) that relies on: 1) a representation of raw-data that models the relational semantics of text by jointly considering objects and relations expressed in a knowledge resource, and 2) an end-to-end neural architecture that learns the query-document relevance by leveraging the distributional and relational semantics of documents and queries. The experimental evaluation carried out on two TREC datasets from TREC Terabyte and TREC CDS tracks relying respectively on WordNet and MeSH resources, indicates that our model outperforms state-of-the-art semantic and deep neural IR models.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to ACM. The definitive version is available at http://dl.acm.org This papers appears in ICTIR '17 ISBN: 978-1-4503-4490-6. The original PDF is available at: https://dl.acm.org/citation.cfm?doid=3121050.3121063
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Other partners > Sorbonne Université (FRANCE)
Other partners > Université Pierre et Marie Curie, Paris 6 - UPMC (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Statistics:download
Deposited By: IRIT IRIT
Deposited On:10 Oct 2018 14:04

Repository Staff Only: item control page