Concept Extraction and Clustering for Topic Digital Library Construction

Chengzhi Zhang, Dan Wu
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引用次数: 15

Abstract

This paper is to introduce a new approach to build topic digital library using concept extraction and document clustering. Firstly, documents in a special domain are automatically produced by document classification approach. Then, the keywords of each document are extracted using the machine learning approach. The keywords are used to cluster the documents subset. The clustered result is the taxonomy of the subset. Lastly, the taxonomy is modified to the hierarchical structure for user navigation by manual adjustments. The topic digital library is constructed after combining the full-text retrieval and hierarchical navigation function.
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面向主题数字图书馆建设的概念提取与聚类
本文提出了一种基于概念抽取和文献聚类的主题数字图书馆构建方法。首先,采用文档分类方法自动生成特定领域的文档。然后,使用机器学习方法提取每个文档的关键字。关键字用于对文档子集进行聚类。聚集的结果是子集的分类。最后,通过手动调整将分类法修改为层次结构,以便用户导航。将全文检索和分层导航功能相结合,构建主题数字图书馆。
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