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...

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Danushka Bollegala, Taiki Honma, Yutaka Matsuo, Mitsuru Ishizuka
• Keywords: Alias Extraction, Candidate Aliases, Internet Technology, Outperforms Numerous Baselines, WWW 2008