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» A clustering method that uses lossy aggregation of data
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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 9 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
ICONIP
2009
13 years 7 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
SP
2002
IEEE
141views Security Privacy» more  SP 2002»
13 years 8 months ago
Collaborative Filtering with Privacy
Server-based collaborative filtering systems have been very successful in e-commerce and in direct recommendation applications. In future, they have many potential applications in...
John F. Canny
DKE
2006
83views more  DKE 2006»
13 years 9 months ago
Bulk insertion for R-trees by seeded clustering
We propose a scalable technique called Seeded Clustering that allows us to maintain R-tree indices by bulk insertion while keeping pace with high data arrival rates. Our approach ...
Taewon Lee, Bongki Moon, Sukho Lee
ICDE
2010
IEEE
273views Database» more  ICDE 2010»
14 years 9 months ago
WikiAnalytics: Ad-hoc Querying of Highly Heterogeneous Structured Data
Searching and extracting meaningful information out of highly heterogeneous datasets is a hot topic that received a lot of attention. However, the existing solutions are based on e...
Andrey Balmin, Emiran Curtmola