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Interval-Valued Fuzzy Extension of Formal Concept Analysis for Information Retrieval

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Neural Information Processing (ICONIP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7663))

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Abstract

In this paper, we propose an information retrieval approach based on interval-valued fuzzy theory which allows to express the total and partial ignorance in the knowledge domain (i.e the incidence matrix). Hence, we propose i) to deal with the presence of partial or total ignorance in the knowledge domain; ii) the application of different interval-valued fuzzy generalized derivations operators to express different queries forms, namely conjunctive and disjunctive queries as well as negation in the queries; iii) the linearization of the lattice structure of formal concepts satisfying a given query based on hamming distance in order to enhance lattice navigation.

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Author information

Authors and Affiliations

  1. Limose, Faculté des Sciences, Université M’hamed Bouguara, Avenue de l’indépendance, Boumerdes, 35000, Algérie

    Loutfi Zerarga

  2. Département d’informatique, Université Mouloud Mammeri, BP 17, RP, Tizi-Ouzou, 15000, Algérie

    Yassine Djouadi

Authors
  1. Loutfi Zerarga
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  2. Yassine Djouadi
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Zerarga, L., Djouadi, Y. (2012). Interval-Valued Fuzzy Extension of Formal Concept Analysis for Information Retrieval. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34475-6_73

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  • DOI: https://doi.org/10.1007/978-3-642-34475-6_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34474-9

  • Online ISBN: 978-3-642-34475-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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