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International Conference on Agents and Artificial Intelligence

ICAART 2014: Agents and Artificial Intelligence pp 280–295Cite as

Combining Semantic Query Disambiguation and Expansion to Improve Intelligent Information Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8946))

Abstract

We show in this paper how Semantic Query Disambiguation (SQD) combined with Semantic Query Expansion (SQE) can improve the effectiveness of intelligent information retrieval. Firstly, we propose and assess a possibilistic-based approach mixing SQD and SQE. This approach is based on corpus analysis using co-occurrence graphs modeled by possibilistic networks. Indeed, our model for relevance judgment uses possibility theory to take advantage of a double measure (possibility and necessity). Secondly, we propose and evaluate a probabilistic circuit-based approach combining SQD and SQE in an intelligent information retrieval context. In this approach, both SQD and SQE tasks are based on a graph data model, in which circuits between its nodes (words) represent the probabilistic scores for their semantic proximities. In order to compare the performance of these two approaches, we perform our experiments using the standard ROMANSEVAL test collection for the SQD task and the CLEF-2003 benchmark for the SQE process in French monolingual information retrieval evaluation. The results show the impact of SQD on SQE based on the recall/precision standard metrics for both the possibilistic and the probabilistic circuit-based approaches. Besides, the results of the possibilistic approach outperform the probabilistic ones, since it takes into account of imprecision cases.

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Acknowledgements

We are grateful to the Evaluations and Language resources Distribution Agency (ELDA) which kindly provided us the Le Monde 94 and ATS 94 document collections of the CLEF 2003 campaign.

Author information

Authors and Affiliations

  1. RIADI Research Laboratory, ENSI Manouba University, 2010, Manouba, Tunisia

    Bilel Elayeb, Oussama Ben Khiroun & Narjès Bellamine Ben Saoud

  2. LISI Laboratory of Computer Science for Industrial Systems, ISD Manouba University, 2010, Manouba, Tunisia

    Ibrahim Bounhas

  3. Emirates College of Technology, P.O. Box: 41009, Abu Dhabi, UAE

    Bilel Elayeb

  4. Higher Institute of Informatics (ISI), Tunis El Manar University, 1002, Tunis, Tunisia

    Narjès Bellamine Ben Saoud

Authors
  1. Bilel Elayeb
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  2. Ibrahim Bounhas
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  3. Oussama Ben Khiroun
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  4. Narjès Bellamine Ben Saoud
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Corresponding author

Correspondence to Bilel Elayeb .

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Editors and Affiliations

  1. LERIA - UFR Sciences, Angers, France

    Béatrice Duval

  2. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  3. LERIA - UFR Sciences, Angers, France

    Stephane Loiseau

  4. INSTICC, Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Elayeb, B., Bounhas, I., Khiroun, O.B., Saoud, N.B.B. (2015). Combining Semantic Query Disambiguation and Expansion to Improve Intelligent Information Retrieval. In: Duval, B., van den Herik, J., Loiseau, S., Filipe, J. (eds) Agents and Artificial Intelligence. ICAART 2014. Lecture Notes in Computer Science(), vol 8946. Springer, Cham. https://doi.org/10.1007/978-3-319-25210-0_17

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  • DOI: https://doi.org/10.1007/978-3-319-25210-0_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25209-4

  • Online ISBN: 978-3-319-25210-0

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