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Exact top-k keyword search on graph databases

Authors:

Meirong Wang,

Lijun Jiang,

Liru Zhang,

Tadashi OhmoriAuthors Info & Claims

SAC '11: Proceedings of the 2011 ACM Symposium on Applied Computing

Pages 985 - 986

https://doi.org/10.1145/1982185.1982400

Published: 21 March 2011 Publication History

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Abstract

In this paper, by modifying an existing graph-database keyword search algorithm DPBF [1] in a straightforward strategy, we propose such an algorithm that can find exact top-k answers, with eliminating redundant answers, in an exact ranked order in O((2^l+1mk + 3^lnk · logk)log(2^lnk)) run time (l: the number of keywords; k: top-k; n: the number of nodes in the graph database; m: the number of edges in the graph database) with the space complexity of O(2^l+1nk).

References

[1]

B. Ding, J. X. Yu, L. Qin, X. Zhang, and X. Lin. Finding Top-k Min-Cost Connected Trees in Databases. In proc. of the 23<sup>rd</sup> International Conference on Data engineering (ICDE'07), 2007, 836--845.

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[2]

H. He, H. Wang, J. Yang and P. S. Yu. BLINKS ranked Keyword Searches on Graphs. In SIGMOD'07, 2007, 305--316.

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[3]

K. Golenberg, B. Kimelfeld and Y. Sagiv. Keyword Proximity Search in Complex Data Graphs. In ACM SIGMOD'08, 2008, 927--940.

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[4]

M. R. Wang, L. R. Zhang and T. Ohmori. A report on Top-k keyword search algorithms with redundancy elimination on graph databases. In IPSJ SIG Technical Report (DBS-151-28) Japan. 2010. Nov.

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Index Terms

Exact top-k keyword search on graph databases
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

SAC '11: Proceedings of the 2011 ACM Symposium on Applied Computing

March 2011

1868 pages

ISBN:9781450301138

DOI:10.1145/1982185

Conference Chairs:
William Chu
Tunghai University, TaiChung, Taiwan
,
W. Eric Wong
University of Texas at Dallas, Richardson, Texas
,
Program Chairs:
Mathew J. Palakal
Indiana University Purdue University, Indianapolis
,
Chih-Cheng Hung
Southern Polytechnic State University, Marietta

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 March 2011

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SAC'11: The 2011 ACM Symposium on Applied Computing

March 21 - 24, 2011

TaiChung, Taiwan

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Answering Top-k Keyword Queries on Relational Databases

Improving the effectiveness of keyword search in databases using query logs

Efficient Top-k Keyword Search on XML Streams

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Answering Top-k Keyword Queries on Relational Databases

Improving the effectiveness of keyword search in databases using query logs

Efficient Top-k Keyword Search on XML Streams

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