Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
SOMLib: a digital library system based on neural networks
Proceedings of the fourth ACM conference on Digital libraries
Modern Information Retrieval
The C-value/NC-value Method of Automatic Recognition for Multi-Word Terms
ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Concept clustering and knowledge integration from a children's dictionary
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Keyword-based document clustering
AsianIR '03 Proceedings of the sixth international workshop on Information retrieval with Asian languages - Volume 11
Using Topic Keyword Clusters for Automatic Document Clustering
IEICE - Transactions on Information and Systems
Toward generic title generation for clustered documents
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Automatically structuring domain knowledge from text: An overview of current research
Information Processing and Management: an International Journal
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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.