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Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases
Joint Authors
Wang, Yingqi
Wang, Nianbin
Zhou, Lianke
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-29
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Due to the ambiguity and impreciseness of keyword query in relational databases, the research on keyword query expansion has attracted wide attention.
Existing query expansion methods expose users’ query intention to a certain extent, but most of them cannot balance the precision and recall.
To address this problem, a novel two-step query expansion approach is proposed based on query recommendation and query interpretation.
First, a probabilistic recommendation algorithm is put forward by constructing a term similarity matrix and Viterbi model.
Second, by using the translation algorithm of triples and construction algorithm of query subgraphs, query keywords are translated to query subgraphs with structural and semantic information.
Finally, experimental results on a real-world dataset demonstrate the effectiveness and rationality of the proposed method.
American Psychological Association (APA)
Wang, Yingqi& Wang, Nianbin& Zhou, Lianke. 2017. Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases. Scientific Programming،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1203469
Modern Language Association (MLA)
Wang, Yingqi…[et al.]. Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases. Scientific Programming No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1203469
American Medical Association (AMA)
Wang, Yingqi& Wang, Nianbin& Zhou, Lianke. Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases. Scientific Programming. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1203469
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203469