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SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
ICONIP
2009
13 years 5 months ago
Text Mining with an Augmented Version of the Bisecting K-Means Algorithm
There is an ever increasing number of electronic documents available today and the task of organizing and categorizing this ever growing corpus of electronic documents has become t...
Yutaro Hatagami, Toshihiko Matsuka
CORR
2004
Springer
122views Education» more  CORR 2004»
13 years 7 months ago
"In vivo" spam filtering: A challenge problem for data mining
Spam, also known as Unsolicited Commercial Email (UCE), is the bane of email communication. Many data mining researchers have addressed the problem of detecting spam, generally by...
Tom Fawcett
ACMSE
2004
ACM
14 years 1 months ago
Topic-based clustering of news articles
Recent years have witnessed an explosion in the availability of news articles on the World Wide Web. Although searchengines’ algorithms have made it easier to locate these docum...
Najaf Ali Shah, Ehab M. ElBahesh
ESANN
2008
13 years 9 months ago
Parallelizing single patch pass clustering
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
Nikolai Alex, Barbara Hammer