Exploiting the Role of Named Entities in Query Oriented Document Summarization
In this paper, we exploit the role of named entities in measuring document/query sentence relevance in query oriented extractive summarization. Named entity driven associations are defined as the informative, semantic sensitive text bi grams consisting of at least one named entity or the semantic class of a named entity. They are extracted automatically according to seven pre defined templates. Question types are also taken into consideration if they are available when dealing with query questions. To alleviate problems with low coverage, named entity based association and uni gram models are integrated together to compensate each other in similarity calculation. Automatic ROUGE evaluations indicate that the proposed idea can produce a very good system that among the best performing system at the DUC 2005.
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