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.
CITATION STYLE
Bollegala, D., Honma, T., Matsuo, Y., & Ishizuka, M. (2008). Mining for personal name aliases on the web. In Proceeding of the 17th International Conference on World Wide Web 2008, WWW’08 (pp. 1107–1108). https://doi.org/10.1145/1367497.1367679
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