Multi-documents Automatic Abstracting based on text clustering and semantic analysis |
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Authors: | Qinglin Guo Ming Zhang |
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Affiliation: | aDepartment of Computer Science and Technology, Peking University, Beijing 100871, China;bSchool of Computer Science and Technology, North China Electric Power University, Beijing 102206, China |
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Abstract: | A method of realization of multi-documents Automatic Abstracting based on text clustering and semantic analysis is brought forward, aimed at overcoming shortages of some current methods about multi-documents. The method makes use of semantic analysis and can realize Automatic Abstracting of multi-documents. The algorithm of twice word segmentation based on the title and first-sentences in paragraphs is brought forward. Its precision and recall is above 95%. For a specific domain on plastics, an Automatic Abstracting system named TCAAS is implemented. The precision and recall of multi-document’s Automatic Abstracting is above 75%. And experiments do prove that it is feasible to use the method to develop a domain Automatic Abstracting system, which is valuable for further study in more depth. |
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Keywords: | Semantic analysis Automatic Abstracting Multi-documents Text clustering Natural language understanding |
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