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Enhancing Cross Document Coreference of Web Documents with Context Similarity and Very Large Scale Text Categorization   
摘  要:   Cross Document Coreference (CDC) is the task of constructing the coreference chain for mentions of a person across a set of documents. This work offers a holistic view of using document-level categories, sub-document level context and extracted entities and relations for the CDC task. We train a categorization component with an efficient flat algorithm using thousands of ODP categories and over a million web documents. We propose to use ranked categories as coreference information, particularly suitable for web documents that are widely different in style and content. An
发  表:   International Conference on Computational Linguistics  2010

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