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International Conference on Contemporary Computing

IC3 2011: Contemporary Computing pp 475–490Cite as

Answering Cross-Source Keyword Queries over Deep Web Data Sources

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 168))

Abstract

A popular trend in data dissemination involves online data sources that are hidden behind query forms, which are part of the deep web. Extracting information across multiple deep web sources in a domain is challenging, but increasingly crucial in many areas. Keyword search, a popular information discovery method, has been studied extensively on the surface web and relational databases. Keyword-based queries can provide a powerful yet intuitive means for accessing data from the deep web as well. However, this involves many challenges. For example, deep web data is hidden behind query interfaces, deep web data sources often contain redundant and/or incomplete data, and there is often inter-dependence among data sources. Thus, it is very hard to automatically execute cross-source queries.

This paper focuses on answering cross-source queries over deep web data sources. In our approach, we model a list of deep web data sources using a graph to capture the dependencies among them, and we consider the problem of answering cross-source queries over these deep web data sources as a graph search problem. We have developed a bidirectional query planning algorithm to generate query plans for two types of cross-source queries, which are entity-attributes queries and entity-entity relationship queries.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Ohio State University, Columbus, OH, 43210, USA

    Fan Wang & Gagan Agrawal

Authors
  1. Fan Wang
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  2. Gagan Agrawal
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Editor information

Editors and Affiliations

  1. Iowa State University and IIT Bombay, India, 329 Durham, Ames, IA 5001, Iowa, USA

    Srinivas Aluru

  2. Indian Statistical Institute, 203 B.T. Road, 700 108, Kolkata, West Bengal, India

    Sanghamitra Bandyopadhyay

  3. The Ohio State University, 3190 Graves Hall, 333 W 10th Ave, 43210, Columbus, OH, USA

    Umit V. Catalyurek

  4. Department of Computing Science, Chalmers University, Rännvagen 6B, 412 96, Göteborg, Sweden

    Devdatt P. Dubhashi

  5. Dept. of Electrical and Computer Engineering, Iowa State University, 329 Durham, IA 50011, Ames, USA

    Phillip H. Jones

  6. TASSL, Dept. of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Brett Road, NJ 08854-8058, Piscataway, USA

    Manish Parashar

  7. School of Computer Engineering, Nanyang Technological University, N4-02a-32 Nanyang Ave, 639798, Singapore

    Bertil Schmidt

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© 2011 Springer-Verlag Berlin Heidelberg

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Wang, F., Agrawal, G. (2011). Answering Cross-Source Keyword Queries over Deep Web Data Sources. In: Aluru, S., et al. Contemporary Computing. IC3 2011. Communications in Computer and Information Science, vol 168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22606-9_47

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  • DOI: https://doi.org/10.1007/978-3-642-22606-9_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22605-2

  • Online ISBN: 978-3-642-22606-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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