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A Big Data Intelligent Search Assistant Based on the Random Neural Network

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Advances in Big Data (INNS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 529))

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Abstract

The need to search for specific information or products in the ever expanding Internet has led the development of Web search engines and recommender systems. Whereas their benefit is the provision of a direct connection between users and the information or products sought within the Big Data, any search outcome will be influenced by a commercial interest as well as by the users’ own ambiguity in formulating their requests or queries. This research analyses the result rank relevance provided by the different Web search engines, metasearch engines, academic databases and recommender systems. We propose an Intelligent Internet Search Assistant (ISA) that acts as an interface between the user and Big Data search engines. We also present a new relevance metric which combines both relevance and rank. We use this metric to validate and compare the performance of our proposed algorithm against other search engines and recommender systems. On average, our ISA outperforms other search engines.

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Acknowledgment

This research has used Groupfilms dataset from the Department of Computer Science and Engineering at the University of Minnesota; Trip Advisor dataset from the University of California-Irvine, Machine Learning repository, Centre for Machine Learning and Intelligent Systems and Amazon dataset from Julian McAuley Computer Science Department at University of California, San Diego.

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Authors and Affiliations

  1. Intelligent Systems and Networks Group, Electrical and Electronic Engineering, Imperial College London, London, UK

    Will Serrano

Authors
  1. Will Serrano
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Corresponding author

Correspondence to Will Serrano .

Editor information

Editors and Affiliations

  1. School of Computing and Communications, Lancaster University , Lancaster, United Kingdom

    Plamen Angelov

  2. Data Engineering Lab, Dept. of Informatics, Aristotle University of Thessaloniki , Thessaloniki, Greece

    Yannis Manolopoulos

  3. Lab of Forest Informatics (FiLAB), Democritus University of Thrace , Orestiada, Greece

    Lazaros Iliadis

  4. WPC Information Systems Faculty, Arizona State University , Tempe, Arizona, USA

    Asim Roy

  5. Electrical Engineering Dept, (ICA), Pontifical Catholic Univ of Rio de Janei , Rio de Janeiro, Rio de Janeiro, Brazil

    Marley Vellasco

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Serrano, W. (2017). A Big Data Intelligent Search Assistant Based on the Random Neural Network. In: Angelov, P., Manolopoulos, Y., Iliadis, L., Roy, A., Vellasco, M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham. https://doi.org/10.1007/978-3-319-47898-2_26

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  • DOI: https://doi.org/10.1007/978-3-319-47898-2_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47897-5

  • Online ISBN: 978-3-319-47898-2

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