Semantic Based Clustering of Web Documents

"Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values," Data Mining and Knowledge Discovery, Vol. “Density-Based Clustering in

The research proposes a data oriented approach for choosing the type of clustering algorithms and a new cluster validity index for choosing their input parameters.. The

In this paper, we have shown that how to construct complementarity functions for the circular cone complementarity problem, and have proposed four classes of merit func- tions for

Numerical experiments indicate that our alternative reconstruction formulas perform significantly better than the standard scaling function series (1.1) for smooth f and are no

In the past researches, all kinds of the clustering algorithms are proposed for dealing with high dimensional data in large data sets.. Nevertheless, almost all of

Additional Key Words and Phrases: Topic Hierarchy Generation, Text Segment, Hierarchical Clustering, Partitioning, Search-Result Snippet, Text Data

For the data sets used in this thesis we find that F-score performs well when the number of features is large, and for small data the two methods using the gradient of the

• Information retrieval : Implementing and Evaluating Search Engines, by Stefan Büttcher, Charles L.A.