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Linking Named Entities in Tweets with Knowledge Base via User Interest Modeling

Linking Named Entities in Tweets with Knowledge Base via User Interest Modeling

This video was recorded at 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago 2013. Twitter has become an increasingly important source of information, with more than 400 million tweets posted per day. The task to link the named entity mentions detected from tweets with the corresponding real world entities in the knowledge base is called tweet entity linking. This task is of practical importance and can facilitate many different tasks, such as personalized recommendation and user interest discovery. The tweet entity linking task is challenging due to the noisy, short, and informal nature of tweets. Previous methods focus on linking entities in Web documents, and largely rely on the context around the entity mention and the topical coherence between entities in... Show More
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