Pictures of relevance: a geometric analysis of similarity measures
Journal of the American Society for Information Science
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
ACM Computing Surveys (CSUR)
Modern Information Retrieval
Learning to cluster web search results
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Object-level ranking: bringing order to Web objects
WWW '05 Proceedings of the 14th international conference on World Wide Web
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
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More and more digital literature emerges on the internet. It is difficult for users to find the information they really need through a simple search due to the amount of electronic literature on the internet. In this article a digital literature search system is described, which contains link analysis, information retrieval and document clustering technology. The system analyses the rank score of literatures based on their attributes and the relationship of them, then feedback the most important literatures according to users' requirement. Besides, this system can group the results by different characters and feed back respectively. It will enhance user's efficiency in literatures retrieval.