Concept Extraction and Clustering for Topic Digital Library Construction

Chengzhi, Zhang and Dan, Wu Concept Extraction and Clustering for Topic Digital Library Construction., 2008 . In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Sydney, Dec, 2008. [Conference paper]

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English 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.

Item type: Conference paper
Keywords: Concept Extraction, Topic Digital Library, Document Clustering
Subjects: I. Information treatment for information services > IC. Index languages, processes and schemes.
I. Information treatment for information services > IB. Content analysis (A and I, class.)
Depositing user: Chengzhi Zhang
Date deposited: 05 Jan 2009
Last modified: 14 Dec 2012 21:24
URI: http://hdl.handle.net/10760/12692

References

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Zhang Chengzhi, Wu Dan. Concept Extraction and Clustering for Topic Digital Library Construction. In: Proceedings of Workshop on Natural Language Processing and Ontology Engineering (NLPOE 2008) in conjunction with Conference on Web Intelligence (WI-08). pp 299-3-2, 2008, Sydney, Australia.


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