Mining for personal name aliases on the web

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Mining for personal name aliases on the web
We propose a novel approach to find aliases of a given name from the web. We exploit a set of known names and their aliases as training data and extract lexical patterns that convey information related to aliases of names from text snippets returned by a web search engine. The patterns are then used to find candidate aliases of a given name. We use anchor texts and hyperlinks to design a word co-occurrence model and define numerous ranking scores to evaluate the association between a name and its candidate aliases. The proposed method outperforms numerous baselines and previous work on alias extraction on a dataset of personal names, achieving a statistically significant mean reciprocal rank of 0.6718. Moreover, the aliases extracted using the proposed method improve recall by 20% in a relation-detection task. Categories and Subject Descriptors H.3.3 [Information Systems]: Information Search and Retrieval General Terms Algorithms Keywords Name alias extraction, Semantic Web, Web Minin...
Danushka Bollegala, Taiki Honma, Yutaka Matsuo, Mi
Added 21 Nov 2009
Updated 21 Nov 2009
Type Conference
Year 2008
Where WWW
Authors Danushka Bollegala, Taiki Honma, Yutaka Matsuo, Mitsuru Ishizuka
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