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International Symposium on Neural Networks

ISNN 2011: Advances in Neural Networks – ISNN 2011 pp 578–586Cite as

Ranked Neuro Fuzzy Inference System (RNFIS) for Information Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6675))

Abstract

The paper presents a novel approach to informational retrieval based on a synergy of knowledge-based models, set theoretic models, and vector space models of domain within a Fuzzy Logic framework. An input query is expanded to multiple synonym queries based on query semantics. Each document in the collection is divided into different zones with different relative importance assigned to each zone indicating its role in the query. Fuzzy rule bases are applied to each zone with parameters derived from vector space models and semantic query expansion. Fuzzy inference procedure outputs the relevance rank of each zone in satisfying the query. The relevance ranks of different zones are aggregated using the Ordered Weighted Averaging (OWA) operator to get the overall relevance rank of the complete document. The documents are ranked according to their relevance. The system has been tested on a standard dataset and has been demonstrated to show improved performance over typical vector space based approaches.

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Author information

Authors and Affiliations

  1. College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad, Pakistan

    Asif Nawaz & Aasia Khanum

Authors
  1. Asif Nawaz
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  2. Aasia Khanum
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Editor information

Editors and Affiliations

  1. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Derong Liu

  2. College of Information Science and Engineering, Shenyang, Northeastern University, 110004, Liaoing, China

    Huaguang Zhang

  3. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios Polycarpou

  4. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  5. Deptartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, RI 02881, Kingston, USA

    Haibo He

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© 2011 Springer-Verlag Berlin Heidelberg

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Nawaz, A., Khanum, A. (2011). Ranked Neuro Fuzzy Inference System (RNFIS) for Information Retrieval. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21105-8_67

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  • DOI: https://doi.org/10.1007/978-3-642-21105-8_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21104-1

  • Online ISBN: 978-3-642-21105-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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