Querying Communities in Relational Databases
Refereed conference paper presented and published in conference proceedings


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摘要Keyword search on relational databases provides users with insights that they can not easily observe using the traditional RDBMS techniques. Here, an l-keyword query is specified by a set of l keywords, {k(1), k(2), ... , k(l)}. It finds how the tuples that contain the keywords are connected in a relational database via the possible foreign key references. Conceptually, it is to find some structural information in a database graph, where nodes are tuples and edges are foreign key references. The existing work studied how to find connected trees for an l-keyword query. However, a tree may only show partial information about how those tuples that contain the keywords are connected. In this paper, we focus on finding communities for an l-keyword query. A community is an induced subgraph that contains all the l-keywords within a given distance. We propose new efficient algorithms to find all/top-k communities which consume small memory, for an l-keyword query. For top-k l-keyword queries, our algorithm allows users to interactively enlarge k at run time. We conducted extensive performance studies using two large real datasets to confirm the efficiency of our algorithms.
著者Qin L, Yu JX, Chang LJ, Tao YF
會議名稱IEEE 25th International Conference on Data Engineering
會議開始日29.03.2009
會議完結日02.04.2009
會議地點Shanghai
會議國家/地區中國
詳細描述IEEE
出版年份2009
月份1
日期1
出版社IEEE
頁次724 - 735
國際標準書號978-1-4244-3422-0
國際標準期刊號1084-4627
語言英式英語
Web of Science 學科類別Computer Science; Computer Science, Software Engineering; Computer Science, Theory & Methods; Engineering; Engineering, Electrical & Electronic

上次更新時間 2020-04-07 於 02:40