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Web appearance, name disambiguation, social network, document clustering, link structure, information bottleneck.
Say you are looking for information about a particular person. A search engine returns many pages for that person's name but which pages are about the person you care about, and which are about other people who happen to have the same name? Furthermore, if we are looking for multiple people who are related in some way, how can we best leverage this social network? This paper presents two unsupervised frameworks for solving this problem: one based on link structure of the Web pages, another using Agglomerative/Conglomerative Double Clustering (A/CDC) --- an application of a recently introduced multi-way distributional clustering method. To evaluate our methods, we collected and hand-labeled a dataset of over 1000 Web pages retrieved from Google queries on 12 personal names appearing together in someones in an email folder. On this dataset our methods outperform traditional agglomerative clustering by more than 20%, achieving over 80% F-measure.
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|2005 DisambiguatingWebAppearancesOfPeople||Ron Bekkerman|
|Disambiguating Web Appearances of People in a Social Network||Proceedings of the 14th International World Wide Web Conference||http://dx.doi.org/10.1145/1060745.1060813||10.1145/1060745.1060813||2005|
|Author||Ron Bekkerman + and Andrew McCallum +|
|journal||Proceedings of the 14th International World Wide Web Conference +|
|title||Disambiguating Web Appearances of People in a Social Network +|