BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Enhanced hypertext categorization using hyperlinks
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
OPTICS: ordering points to identify the clustering structure
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Data mining and the Web: past, present and future
Proceedings of the 2nd international workshop on Web information and data management
ACM SIGKDD Explorations Newsletter
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
STING: A Statistical Information Grid Approach to Spatial Data Mining
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Data mining for hypertext: a tutorial survey
ACM SIGKDD Explorations Newsletter
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Web-Log Mining for Predictive Web Caching
IEEE Transactions on Knowledge and Data Engineering
Effectively Finding Relevant Web Pages from Linkage Information
IEEE Transactions on Knowledge and Data Engineering
Model-Based Clustering and Visualization of Navigation Patterns on a Web Site
Data Mining and Knowledge Discovery
Similarity-based clustering of Web transactions
Proceedings of the 2003 ACM symposium on Applied computing
Learning Rules for Conceptual Structure on the Web
Journal of Intelligent Information Systems
The web as a graph: measurements, models, and methods
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
An evolutionary data clustering algorithm
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Spatial clustering and outlier analysis for the regionalization of maize cultivation in China
WSEAS Transactions on Information Science and Applications
Spatial clustering for the regionalization of maize cultivation in China and its outlier analysis
WSEAS Transactions on Information Science and Applications
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Clustering is the process of grouping objects together in such a way that the objects belonging to the same group are similar and those belonging to different groups are dissimilar. Clustering technique can be used in many applications for example biological, financial applications and many more. One of these application types is Web clustering where different types of objects can be clustered into different groups for various purposes. This paper deals with the different aspects of Web data mining and provides an overview about the various techniques used in this field.