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A Probabilistic Model for Linking Named Entities in Web Text with Heterogeneous Information Networks

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Executive Summary

Heterogeneous information networks that consist of multi-type, interconnected objects are becoming ubiquitous and increasingly popular, such as social media networks and bibliographic networks. The task to link named entity mentions detected from the unstructured Web text with their corresponding entities existing in a heterogeneous information network is of practical importance for the problem of information network population and enrichment. This task is challenging due to name ambiguity and limited knowledge existing in the information network.

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