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dc.contributor.advisor林坤辉
dc.contributor.author许振团
dc.date.accessioned2018-12-05T01:35:10Z
dc.date.available2018-12-05T01:35:10Z
dc.date.issued2018-01-03
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/169775
dc.description.abstract迈入二十一世纪,伴随着科技的不断进步和互联网的高速发展,各类的信息资源成倍快速增加。人们迫切地希望能快速的、准确的从庞大的信息源中寻找到对自己真正有用的资料。关键词能够高度归纳文档的内容,并且反映文档的主题,为人们寻找资源提供有力的帮助。 目前大部分的文本资源没有提供关键词。虽然人工标注关键词往往拥有较高的准确性,但是因为标注者的学识储备、理解程度差异以及总结概括能力不尽相同,往往带有较强的主观性。况且,其需要花费较多时间阅读、理解文本,这显然无法满足如今信息资源快速增长的速度。关键词提取技术由此出现,其能很好地处理这个难题。建立统一的标准,借助于计算机的快速处理能力,自动提取关键词,可以...
dc.description.abstractInto the twenty-first century, with the continuous progress of technology and the rapid development of the Internet, various types of information resources doubled rapidly. People are eager to be able to quickly and accurately from a huge source of information to find own really useful information. Keywords can highly induce the content of the document and reflect the theme of the document, it wil...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=59077&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=59657
dc.subject关键词提取
dc.subject主题结构
dc.subject语义相似度
dc.subjectKeyword Extraction
dc.subjectTopic Structure
dc.subjectSemantic Similarity
dc.title基于文档主题结构与语义的中文文本关键词提取算法研究
dc.title.alternativeResearch on Keyword Extraction Algorithm for Chinese Text Based on Document Topic Structure and Semantics
dc.typethesis
dc.date.replied2017-05-12
dc.description.note学位:工学硕士
dc.description.note院系专业:软件学院_软件工程
dc.description.note学号:24320141152409


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