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Understanding Query Interfaces by Statistical Parsing

  • Yafei Li
  • , Jing Zhao
  • , Tianqiang Huang
  • , Weifeng Su
  • , Hongmin Cai
  • , Hejun Wu*
  • , Frederick H. Lochovsky*
  • *Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

Abstract

Users submit queries to an online database via its query interface. Query interface parsing, which is important for many applications, understands the query capabilities of a query interface. Since most query interfaces are organized hierarchically, we present a novel query interface parsing method, StatParser (Statistical Parser), to automatically extract the hierarchical query capabilities of query interfaces. StatParser automatically learns from a set of parsed query interfaces and parses new query interfaces. StatParser starts from a small grammar and enhances the grammar with a set of probabilities learned from parsed query interfaces under the maximum-entropy principle. Given a new query interface, the probability-enhanced grammar identifies the parse tree with the largest global probability to be the query capabilities of the query interface. Experimental results show that StatParser very accurately extracts the query capabilities and can effectively overcome the problems of existing query interface parsers. © 2013 ACM.
Original languageEnglish
Article number8
Pages (from-to)1-22
JournalACM Transactions on the Web
Volumev. 7
DOIs
Publication statusPublished - May 2013

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