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- Title
Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases.
- Authors
Wang, Yingqi; Wang, Nianbin; Zhou, Lianke
- Abstract
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.
- Subjects
KEYWORD searching; RELATIONAL databases; SQL; VITERBI decoding; BIG data
- Publication
Scientific Programming, 2017, p1
- ISSN
1058-9244
- Publication type
Article
- DOI
10.1155/2017/7613026