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The Research and the Applications of Automatic Summarization Technology
Author: ChaiXiaoLi
Tutor: CuiGuangCai
School: Changchun University of Science and Technology
Course: Computer Software and Theory
Keywords: Automatic Summarization Text Concept vector space model Natural Language Processing
CLC: TP391.1
Type: Master's thesis
Year: 2007
Downloads: 228
Quote: 4
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Abstract
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With the social progress and the development of Internet technology , the sharp increase in amount of network information frequently faced with the explosion of information in today's society . When the flock to the people a lot of information like a tidal wave , the traditional means of manual processing information has been inadequate. To solve this problem , the scientific community technology Abstract automatically generated . Automatic summarization is often seen as a task for natural language processing . Digest is accurate to reflect the core content of a particular article concise and coherent essay , compared with the index to better meet the requirements of access to information . Our automatic summarization technology is still in its early stages , but this technology has an important role can not be underestimated , and has been widely used in the field of information processing will . This thesis is based on the current research status quo , the use of the method of statistical natural language processing , automatic segmentation is the first article , the use of stop words table to filter the segmentation results and use the ( optional on HowNet ) concept , the establishment of the concept of vector space model . By calculating the degree of importance of the important words , and sentences , the system has been a rough Digest . Finally redundant computation , get this article Digest . In this paper , on the basis of these studies , design automatic summarization system based on the concept of vector space model , the machine automatically generated Digest function of each module , confirmed In this paper, the concept of statistical methods based on word frequency statistics digest , more accurately with had a central element of the original article .
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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