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]
Download (265kB) | Preview
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:||02 Oct 2014 12:13|
Actions (login required)