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dc.titleAn effective object-level XML keyword search
dc.contributor.authorBao, Z.
dc.contributor.authorLu, J.
dc.contributor.authorLing, T.W.
dc.contributor.authorXu, L.
dc.contributor.authorWu, H.
dc.identifier.citationBao, Z.,Lu, J.,Ling, T.W.,Xu, L.,Wu, H. (2010). An effective object-level XML keyword search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5981 LNCS (PART 1) : 93-109. ScholarBank@NUS Repository. <a href="" target="_blank"></a>
dc.description.abstractKeyword search is widely recognized as a convenient way to retrieve information from XML data. In order to precisely meet users' search concerns, we study how to effectively return the targets that users intend to search for. We model XML document as a set of interconnected object-trees, where each object contains a subtree to represent a concept in the real world. Based on this model, we propose object-level matching semantics called Interested Single Object (ISO) and Interested Rel ated Object (IRO) to capture single object and multiple objects as user's search targets respectively, and design a novel relevance oriented ranking framework for the matching results. We propose efficient algorithms to compute and rank the query results in one phase. Finally, comprehensive experiments show the efficiency and effectiveness of our approach, and an online demo of our system on DBLP data is available at © Springer-Verlag Berlin Heidelberg 2010.
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume5981 LNCS
dc.description.issuePART 1
Appears in Collections:Staff Publications

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