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Scalable Top-k Keyword Search in Relational Databases

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Database Systems for Advanced Applications (DASFAA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7239))

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Abstract

Keyword search in relational databases has been widely studied in recent years because it does not require users neither to master a certain structured query language nor to know the complex underlying database schemas. There would be a huge number of valid results for a keyword query in a large database. However, only the top 10 or 20 most relevant matches for the keyword query –according to some definition of “Relevance”– are generally of interest. In this paper, we propose an efficient method for answering top-k keyword queries over relational databases. The proposed method is built on an existing scheme of keyword search on relational data streams, but incorporates the ranking mechanisms into the query processing methods and makes two improvements to support top-k keyword search in relational databases. Experimental results validate the effectiveness and efficiency of the proposed method.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Tongji University, Shanghai, 201804, China

    Yanwei Xu & Jihong Guan

  2. Information Technology Center, Nagoya University, Nagoya-shi, 464-8601, Japan

    Yoshiharu Ishikawa

  3. Graduate School of Information Science, Nagoya University, Nagoya-shi, 464-8601, Japan

    Yoshiharu Ishikawa

  4. National Institute of Informatics, Chiyoda-ku, Tokyo, 101-8430, Japan

    Yoshiharu Ishikawa

Authors
  1. Yanwei Xu
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  2. Jihong Guan
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  3. Yoshiharu Ishikawa
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Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, Gwanak-ro, Gwanak-gu, 151747, Seoul, South Korea

    Sang-goo Lee

  2. Computer School, Wuhan University, Luo-jia-shan, Wuchang, 430081, Wuhan, Hubei Province, China

    Zhiyong Peng

  3. School of Information Technology and Electrical Engineering, University of Queensland, 4072, Brisbane, QLD, Australia

    Xiaofang Zhou

  4. Department of Computer Science, Kangwon National University, 192-1, Hyoja2-Dong, 200701, Chuncheon, Kangwon, South Korea

    Yang-Sae Moon

  5. Institute for Computer Science and Business Information, University of Duisburg-Essen, Schützenbahn 70, 45117, Essen, Germany

    Rainer Unland

  6. School of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, 4072, Cheongju, Chungbuk, South Korea

    Jaesoo Yoo

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© 2012 Springer-Verlag Berlin Heidelberg

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Xu, Y., Guan, J., Ishikawa, Y. (2012). Scalable Top-k Keyword Search in Relational Databases. In: Lee, Sg., Peng, Z., Zhou, X., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29035-0_5

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  • DOI: https://doi.org/10.1007/978-3-642-29035-0_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29034-3

  • Online ISBN: 978-3-642-29035-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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