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 de.ne 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.
Name alias extraction Semantic Web Web Mining
Danushka Bollegala Taiki Honma Yutaka Matsuo Mitsuru Ishizuka
The University of Tokyo, Hongo 7-3-1, Tokyo, 113-8656, Japan
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）