Skip to main content.

Posters


Track: Posters

Paper Title:
Mining for Personal Name Aliases on the Web

Authors:

Abstract:
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.

PDF version












Inquiries can be sent to: Email contact: program-chairs at www2008.org

Valid XHTML 1.0 Transitional