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Personalizing Fuzzy Search Criteria for Improving User-Based Flexible Search

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Human Interaction, Emerging Technologies and Future Applications IV (IHIET-AI 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1378))

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Abstract

This proposal provides a user-friendly way of personalizing fuzzy search criteria in an expressive searching platform. The interest is in, for example, if we have a fuzzy criterion “expensive” for searching expensive restaurants defined in the system, by personalization, any user can access the criterion and personalize it with his/her preferences and values that satisfies his/her needs. In this way, every user retrieves different results while querying over a single fuzzy search criterion. The system executes this personalized fuzzy searching criterion if the logged-in user has previously personalized that criterion definition. Moreover, our framework is user-friendly enough to perform expressive searches over modern and conventional database formats without knowing the low-level syntax of the criteria of the framework. Furthermore, we present the architecture of this novel framework, with its design and implementation details. We provide a clarifying case study on our system by providing an experiment. We have analyzed the results obtained from the experiment to show our system’s behavior and performance after incorporating the functionality of the personalization of fuzzy search criteria.

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Authors and Affiliations

  1. Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus de Montegancedo s/n, 28660, Boadilla del Monte, Madrid, Spain

    Mohammad Halim Deedar & Susana Muñoz-Hernández

Authors
  1. Mohammad Halim Deedar
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  2. Susana Muñoz-Hernández
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Correspondence to Mohammad Halim Deedar .

Editor information

Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

  2. Campus du Moulin de la Housse, Université de Reims Champagne-Ardenne GRESPI, Reims Cedex 2, France

    Redha Taiar

  3. Directrice Hôpitaux Universitaires de Strasbourg, IFMK, Strasbourg, France

    Fabienne Groff

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Deedar, M.H., Muñoz-Hernández, S. (2021). Personalizing Fuzzy Search Criteria for Improving User-Based Flexible Search. In: Ahram, T., Taiar, R., Groff, F. (eds) Human Interaction, Emerging Technologies and Future Applications IV. IHIET-AI 2021. Advances in Intelligent Systems and Computing, vol 1378. Springer, Cham. https://doi.org/10.1007/978-3-030-74009-2_24

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