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Building of an Information Retrieval System Based on Genetic Algorithms

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Mobile, Secure, and Programmable Networking (MSPN 2017)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10566))

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Abstract

In an information retrieval system (IRS) the query plays a very important role, so the user of an IRS must write his query well to have the expected result.

In this paper, we have developed a new genetic algorithm-based query optimization method on relevance feedback for information retrieval. By using this technique, we have designed a fitness function respecting the order in which the relevant documents are retrieved, the terms of the relevant documents, and the terms of the irrelevant documents.

Based on three benchmark test collections Cranfield, Medline and CACM, experiments have been carried out to compare our method with three well-known query optimization methods on relevance feedback. The experiments show that our method can achieve better results.

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Author information

Authors and Affiliations

  1. Faculty of Sciences and Technics, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Badr Hssina, Soukaina Lamkhantar, Mohammed Erritali, Abdelkrim Merbouha & Youness Madani

Authors
  1. Badr Hssina
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  2. Soukaina Lamkhantar
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  3. Mohammed Erritali
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  4. Abdelkrim Merbouha
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  5. Youness Madani
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Corresponding author

Correspondence to Badr Hssina .

Editor information

Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Paris, France

    Samia Bouzefrane

  2. Birla Institute of Technology, Mesra, India

    Soumya Banerjee

  3. Conservatoire National des Arts et Métiers, Paris, France

    Françoise Sailhan

  4. Conservatoire National des Arts et Métiers, Paris, France

    Selma Boumerdassi

  5. Institut Mines-Télécom, Evry, France

    Eric Renault

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Hssina, B., Lamkhantar, S., Erritali, M., Merbouha, A., Madani, Y. (2017). Building of an Information Retrieval System Based on Genetic Algorithms. In: Bouzefrane, S., Banerjee, S., Sailhan, F., Boumerdassi, S., Renault, E. (eds) Mobile, Secure, and Programmable Networking. MSPN 2017. Lecture Notes in Computer Science(), vol 10566. Springer, Cham. https://doi.org/10.1007/978-3-319-67807-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-67807-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67806-1

  • Online ISBN: 978-3-319-67807-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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