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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/2454

Title: Collective annotation of Wikipedia entities in web text
Authors: KULKARNI, S
SINGH, A
RAMAKRISHNAN, G
CHAKRABARTI, S
Issue Date: 2009
Publisher: ASSOC COMPUTING MACHINERY
Citation: KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING,457-465
Abstract: To take the first step beyond keyword-based search toward entity-based search, suitable token spans ("spots") on documents must be identified as references to real-world entities from an entity catalog. Several systems have been proposed to link spots on Web pages to entities in Wikipedia. They axe largely based on local compatibility between the text around the spot and textual metadata associated with the entity. Two recent systems exploit inter-label dependencies, but in limited ways. We propose a general collective disambiguation approach. Our premise is that coherent documents refer to entities front one or a few related topics or domains. We give formulations for the trade-off between local spot-to-entity compatibility and measures of global coherence between entities. Optimizing the overall entity assignment is NP-hard. We investigate practical solutions based on local hill-climbing, rounding integer linear programs, and pre-clustering entities followed by local optimization within clusters. In experiments involving over a hundred manually-annotated Web pages and tens of thousands of spots, our approaches significantly outperform recently-proposed algorithms.
URI: http://dspace.library.iitb.ac.in/xmlui/handle/10054/15789
http://hdl.handle.net/100/2454
ISBN: 978-1-60558-495-9
Appears in Collections:Proceedings papers

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