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dc.contributor.authorNaseriparsa, Mehdi
dc.contributor.authorIslam, Md Saiful
dc.contributor.authorLiu, Chengfei
dc.contributor.authorMoser, Irene
dc.date.accessioned2017-11-01T22:22:27Z
dc.date.available2017-11-01T22:22:27Z
dc.date.issued2018
dc.identifier.issn1386-145X
dc.identifier.doi10.1007/s11280-017-0503-8
dc.identifier.urihttp://hdl.handle.net/10072/350464
dc.description.abstractUsers are rarely familiar with the content of a data source they are querying, and therefore cannot avoid using keywords that do not exist in the data source. Traditional systems may respond with an empty result, causing dissatisfaction, while the data source in effect holds semantically related content. In this paper we study this no-but-semantic-match problem on XML keyword search and propose a solution which enables us to present the top-k semantically related results to the user. Our solution involves two steps: (a) extracting semantically related candidate queries from the original query and (b) processing candidate queries and retrieving the top-k semantically related results. Candidate queries are generated by replacement of non-mapped keywords with candidate keywords obtained from an ontological knowledge base. Candidate results are scored using their cohesiveness and their similarity to the original query. Since the number of queries to process can be large, with each result having to be analyzed, we propose pruning techniques to retrieve the top-k results efficiently. We develop two query processing algorithms based on our pruning techniques. Further, we exploit a property of the candidate queries to propose a technique for processing multiple queries in batch, which improves the performance substantially. Extensive experiments on two real datasets verify the effectiveness and efficiency of the proposed approaches.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto35
dc.relation.ispartofjournalWorld Wide Web
dc.subject.fieldofresearchInformation Systems not elsewhere classified
dc.subject.fieldofresearchData Format
dc.subject.fieldofresearchDistributed Computing
dc.subject.fieldofresearchInformation Systems
dc.subject.fieldofresearchcode080699
dc.subject.fieldofresearchcode0804
dc.subject.fieldofresearchcode0805
dc.subject.fieldofresearchcode0806
dc.titleNo-but-semantic-match: computing semantically matched xml keyword search results
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dc.description.versionAccepted Manuscript (AM)
gro.description.notepublicThis publication has been entered into Griffith Research Online as an Advanced Online Version.
gro.rights.copyright© 2017 Springer Netherlands. This is an electronic version of an article published in World Wide Web, 2017, pp 1–35. World Wide Web is available online at: http://link.springer.com/ with the open URL of your article.
gro.hasfulltextFull Text
gro.griffith.authorIslam, Saiful


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