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QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques

Summary: QUEST combines semantic and ML to translate keyword queries into SQL over relational data. Forward mappings to terms and a backward path-join are fused by Dempster-Shafer theory, delivering robust results with little training data and hidden data sources (Deep Web). (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10578
Venue
VLDB
Year
2013
Pagerank
0.00010916417
Overall Rank
1,687 | 88.27%
DOI
-

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,796 Summary Graphs for Relational Database Schemas 2011 VLDB 0.00010524897
3,758 Keyword Search over Relational Databases: A Metadata Approach 2011 SIGMOD 6.7824746e-05
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