An integrated fact/document information system for office automation
Information Technology Research Development Applications - Lecture notes in computer science 178
Database machines and database management
Database machines and database management
User-oriented document clustering: a framework for learning in information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
An automatic and tunable document indexing system
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
Concepts of the cover coefficient-based clustering methodology
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Generation and search of clustered files
ACM Transactions on Database Systems (TODS)
SIGIR '83 Proceedings of the 6th annual international ACM SIGIR conference on Research and development in information retrieval
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Dynamic information and library processing
Dynamic information and library processing
Incremental clustering for dynamic information processing
ACM Transactions on Information Systems (TOIS)
Incremental clustering and dynamic information retrieval
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
A k-mean clustering algorithm for mixed numeric and categorical data
Data & Knowledge Engineering
Streaming cross document entity coreference resolution
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
SIC-means: a semi-fuzzy approach for clustering data streams using c-means
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Algorithm for fuzzy clustering of mixed data with numeric and categorical attributes
ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
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Partitioning by clustering of very large databases is a necessity to reduce the space/time complexity of retrieval operations. However, the contemporary and modern retrieval environments demand dynamic maintenance of clusters. A new cluster maintenance strategy is proposed and its similarity/stability characteristics, cost analysis, and retrieval behavior in comparison with unclustered and completely reclustered database environments have been examined by means of a series of experiments.