| 一种基于主题和分众分类的信息检索优化方法 |
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| 引用本文： | 李超.一种基于主题和分众分类的信息检索优化方法[J].情报理论与实践,2009,32(10). |
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| 作者姓名： | 李超 |
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| 作者单位： | 解放军南京政治学院,上海分院军事信息管理系,上海,200433 |
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| 摘 要： | 本文针对目前搜索引擎存在的检索结果缺乏组织导致检准率不高的问题,提出一种基于主题和分众分类的信息检索优化方法.首先对用户检索主题进行获取和表达,然后以社会标签为聚类项,采用向量空间模型实现基于分众分类的文档主题聚类,并将检索结果按相似度和标签"受欢迎度"复合排序,达到提高检索准确率和优化检索的效果.
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| 关 键 词： | 信息检索 分众分类 向量空间模型 最优化方法 |
An Improved Information Retrieval Method Based on Search Topic and Folksonomy |
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| Li Chao.An Improved Information Retrieval Method Based on Search Topic and Folksonomy[J].Information Studies:Theory & Application,2009,32(10). |
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| Authors: | Li Chao |
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| Abstract: | Due to the low pertinency ratio resulting from the lack of organization of retrieval results in current search engines,this paper proposes an improved information retrieval method based on user's search topic and folksonomy.First,the paper obtains and expresses the user's search topic,then,by taking social tags as clustering options,uses SVM model to implement document topic clustering based on folksonomy.Finally,the retrieval results are sorted in a multiple way in accordance with similarity and tag "popul... |
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| Keywords: | information retrieval folksonomy SVM optimization method |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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