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This talk introduces the problem of matching web-scale entity graphs, such as multilingual name graphs and social network graphs, to solve difficult problems such as name translation or social id finding. While existing approaches focus on using textual (or phonetic) similarity or Web co-occurrences, this approach combines the strength of the two and significantly outperforms the state-of-the-arts. We present our evaluation results using real-life entity graphs.
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