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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/1630

Title: Bidirectional expansion for keyword search on graph databases
Keywords: keyword search
graph theory
relational database systems
edge detection
data graph
Issue Date: 2005
Publisher: Association for Computing Machinery
Citation: Proceedings of the 31st International Conference on Very Large Data Bases, (VLDB), Trondheim, Norway, 30 Augest - 2 September 2005, 505-516
Abstract: Relational, XML and HTML data can be represented as graphs with entities as nodes and relationships as edges. Text is associated with nodes and possibly edges. Keyword search on such graphs has received much attention lately. A central problem in this scenario is to efficiently extract from the data graph a small number of the "best" answer trees. A Backward Expanding search, starting at nodes matching keywords and working up toward confluent roots, is commonly used for predominantly text-driven queries. But it can perform poorly if some keywords match many nodes, or some node has very large degree.In this paper we propose a new search algorithm, Bidirectional Search, which improves on Backward Expanding search by allowing forward search from potential roots towards leaves. To exploit this flexibility, we devise a novel search frontier prioritization technique based on spreading activation. We present a performance study on real data, establishing that Bidirectional Search significantly outperforms Backward Expanding search.
URI: http://hdl.handle.net/10054/1630
ISBN: 1-59593-154-6
Appears in Collections:Proceedings papers

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