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http://dx.doi.org/10.5392/JKCA.2016.16.06.205

A Method for Non-redundant Keyword Search over Graph Data  

Park, Chang-Sup (동덕여자대학교 컴퓨터학과)
Publication Information
The Journal of the Korea Contents Association / v.16, no.6, 2016 , pp. 205-214 More about this Journal
Abstract
As a large amount of graph-structured data is widely used in various applications such as social networks, semantic web, and bio-informatics, keyword-based search over graph data has been getting a lot of attention. In this paper, we propose an efficient method for keyword search over graph data to find a set of top-k answers that are relevant as well as non-redundant in structure. We define a non-redundant answer structure for a keyword query and a relevance measure for the answer. We suggest a new indexing scheme on the relevant paths between nodes and keyword terms in the graph, and also propose a query processing algorithm to find top-k non-redundant answers efficiently by exploiting the pre-calculated indexes. We present effectiveness and efficiency of the proposed approach compared to the previous method by conducting an experiment using a real dataset.
Keywords
Graph Data; Keyword Search; Top-k Query Processing;
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1 T. Tran, S. Rudolph, P. Cimiano, and H. Wang, "Top-k exploration of query candidates for efficient keyword search on graph-shaped (RDF) data," Proc. of the 25th ICDE, pp.405-416, 2009.
2 M. Kargar and A. An, "Keyword search in graphs: finding r-cliques," Proc. of the VLDB Endowment, Vol.4, No.10, pp.681-692, 2011.
3 C. Park and S. Lim, "Efficient processing of keyword queries over graph databases for finding effective answers," Information Proc. and Mgmt, Vol.51, No.1, pp.42-57, 2015.   DOI
4 J. X. Yu, L. Qin, and L. Chang, "Keyword search in relational databases: a survey," Bulletin of the IEEE CS Technical Committee on Data Engineering, Vol.33, No.1, pp.67-78, 2010.
5 R. Fagin, A. Lotem, and M. Naor, "Optimal aggregation algorithms for middleware," Journal of Computer and System Sciences, Vol.66, No.4, pp.614-656, 2003.   DOI
6 S. Buttcher, C. Clarke, and G. Cormack, Information retrieval: implementing and evaluating search engine, MIT Press, 2010.
7 G. Bhalotia, A. Hulgeri, C. Nakhe, S. Chakrabarti, and S. Sudarshan, "Keyword searching and browsing in databases using BANKS," Proc. of ICDE, pp.431-440, 2002.
8 V. Kacholia, S. Pandit, S. Chakrabarti, S. Sudarshan, R. Desai, and H. Karambelkar, "Bidirectional expansion for keyword search on graph databases," Proc. of the 31st Int. Conf. on VLDB, pp.505-516, 2005.
9 H. He, H. Wang, J. Yang, and P. S. Yu, "BLINKS: ranked keyword searches on graphs," ACM SIGMOD Conference, pp.305-316, 2007.
10 B. Ding, J. X. Yu, S. Wang, L. Qin, X. Zhang, and X. Lin, "Finding top-k min-cost connected trees in databases," Proc. of ICDE, pp.836-845, 2007.
11 B. B. Dalvi, M. Kshirsagar, and S. Sudarshan, "Keyword search on external memory data graphs," Proc. of the VLDB Endowment, Vol.1, No.1, pp.1189-1204, 2008.
12 K. Golenberg, B. Kimelfeld, and Y. Sagiv, "Keyword proximity search in complex data graphs," Proc. of ACM SIGMOD Conference, pp.927-940, 2008.
13 L. Qin, J. X. Yu, L. Chang, and Y. Tao, "Querying communities in relational databases," Proc. of the 25th ICDE, pp.724-735, 2009.