The effectiveness and efficiency of agglomerative hierarchic clustering in document retrieval
The effectiveness and efficiency of agglomerative hierarchic clustering in document retrieval
Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
An algorithm for drawing general undirected graphs
Information Processing Letters
Scalable Internet resource discovery: research problems and approaches
Communications of the ACM
Highlights: language- and domain-independent automatic indexing terms for abstracting
Journal of the American Society for Information Science
Information Processing and Management: an International Journal
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Customizable multi-engine search tool with clustering
Selected papers from the sixth international conference on World Wide Web
The SOMLib Digital Library System
ECDL '99 Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
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The recent explosion of the internet has made digital libraries popular. The user-friendly interface of Web browsers allows a user much easier access to the digital library. However, to retrieve relevant documents from the digital library, the user is provided with a search interface consisting of one input field and one push button. Most users type in a single keyword, click the button, and hope for the best. The result of a query using this kind of search interface can consist of a large unordered set of documents, or a ranked list of documents based on the frequency of the keywords. Both lists can contain articles unrelated to user's inquiry unless a sophisticated search was performed and the user knows exactly what to look for. More sophisticated algorithms for ranking the relevance of search results may help, but what is desperately needed are software tools that can analyze the search result and manipulate large hierarchies of data graphically. In this paper, we present a language-independent document classification system for the Florida Center for Library Automation to help users analyze the search query results. Easy access through the Web is provided, as well as a graphical user interface to display the classification results.