Spark: Top-k keyword query in relational databases

Luo, Yi, Lin, Xuemin, Wang, Wei and Zhou, Xiaofang (2007). Spark: Top-k keyword query in relational databases. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data. International Conference on Management of Data (SIGMOD 2007), Beijing, China, (115-126). 11-14 June 2007. doi:10.1145/1247480.1247495

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Author Luo, Yi
Lin, Xuemin
Wang, Wei
Zhou, Xiaofang
Title of paper Spark: Top-k keyword query in relational databases
Formatted title
Spark: Top-κ keyword query in relational databases
Conference name International Conference on Management of Data (SIGMOD 2007)
Conference location Beijing, China
Conference dates 11-14 June 2007
Proceedings title Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data   Check publisher's open access policy
Journal name Proceedings of the ACM SIGMOD International Conference on Management of Data   Check publisher's open access policy
Place of Publication New York, U.S.A.
Publisher Association for Computing Machinery (ACM)
Publication Year 2007
Sub-type Fully published paper
DOI 10.1145/1247480.1247495
ISBN 9781595936868
1595936866
ISSN 0730-8078
Start page 115
End page 126
Total pages 12
Language eng
Formatted Abstract/Summary
With the increasing amount of text data stored in relational databases, there is a demand for RDBMS to support keyword queries over text data. As a search result is often assembled from multiple relational tables, traditional IR-style ranking and query evaluation methods cannot be applied directly.

In this paper, we study the effectiveness and the efficiency issues of answering top-k keyword query in relational database systems. We propose a new ranking formula by adapting existing IR techniques based on a natural notion of virtual document. Compared with previous approaches, our new ranking method is simple yet effective, and agrees with human perceptions. We also study efficient query processing methods for the new ranking method, and propose algorithms that have minimal accesses to the database. We have conducted extensive experiments on large-scale real databases using two popular RDBMSs. The experimental results demonstrate significant improvement to the alternative approaches in terms of retrieval effectiveness and efficiency.
Subjects 080604 Database Management
Keyword Top-k keyword query
Keyword search
Relational database
Query processing methods
Retrieval effectiveness
Information retrieval
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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Created: Mon, 30 Mar 2009, 16:18:51 EST by Maryanne Watson on behalf of School of Information Technol and Elec Engineering