OREGON STATE UNIVERSITY

You are here

EXTRUCT: using deep structural information in XML keyword search

TitleEXTRUCT: using deep structural information in XML keyword search
Publication TypeJournal Article
Year of Publication2010
AuthorsTermehchy, A., and M. Winslett
JournalProc. VLDB Endow.
Volume3
Issue2
Pagination1593–1596
Date Published09/2010
ISSN2150-8097
Abstract

Users who are unfamiliar with database query languages can search XML data sets using keyword queries. Previous work has shown that current XML keyword search methods, although intuitive, do not effectively use the data's structural information and provide poor precision, recall, and ranking for most queries. Based on an extension of the concept of information theory, we have developed principled frameworks called normalized total correlation (NTC) and normalized term presence correlation (NTPC) to measure the relevance of candidate answers to keyword queries. We demonstrate EXTRUCT, an XML keyword search interface that uses NTC and NTPC. An extensive empirical evaluation over two real-world XML DBs has shown that EX-TRUCT has better precision and recall and provides better ranking than all previous approaches. We demonstrate EXTRUCT, along with seven other keyword search systems for four real-world XML data sets, using prepared queries as well as queries from the audience. The demonstration shows that using deep structural information increases the effectiveness of XML keyword search systems considerably.

URLhttp://dl.acm.org/citation.cfm?id=1920841.1921047