Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-319-05813-9-21
Title: Object semantics for XML keyword search
Authors: Le, T.N.
Ling, T.W. 
Jagadish, H.V.
Lu, J.
Issue Date: 2014
Citation: Le, T.N.,Ling, T.W.,Jagadish, H.V.,Lu, J. (2014). Object semantics for XML keyword search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8422 LNCS (PART 2) : 311-327. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-319-05813-9-21
Abstract: It is well known that some XML elements correspond to objects (in the sense of object-orientation) and others do not. The question we consider in this paper is what benefits we can derive from paying attention to such object semantics, particularly for the problem of keyword queries. Keyword queries against XML data have been studied extensively in recent years, with several lowest-common-ancestor based schemes proposed for this purpose, including SLCA, MLCA, VLCA, and ELCA. It can be seen that identifying objects can help these techniques return more meaningful answers than just the LCA node (or subtree) by returning objects instead of nodes. It is more interesting to see that object semantics can also be used to benefit the search itself. For this purpose, we introduce a novel Nearest Common Object Node semantics (NCON), which includes not just common object ancestors but also common object descendants. We have developed XRich, a system for our NCON-based approach, and used it in our extensive experimental evaluation. The experimental results show that our proposed approach outperforms the state-of-the-art approaches in terms of both effectiveness and efficiency. © 2014 Springer International Publishing Switzerland.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/78261
ISSN: 16113349
DOI: 10.1007/978-3-319-05813-9-21
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

67
checked on Sep 28, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.