An effective object-level XML keyword search

Authors:
Zhifeng Bao;Jiaheng Lu;Tok Wang Ling;Liang Xu;Huayu Wu
Affiliations:
School of Computing, National University of Singapore;School of Information, Renmin University of China;School of Computing, National University of Singapore;School of Computing, National University of Singapore;School of Computing, National University of Singapore
Venue:
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Year:
2010

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Abstract

Keyword 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 Related 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 http://xmldb.ddns.comp.nus.edu.sg.