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SIGIR
2002
ACM
13 years 7 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby
WWW
2007
ACM
14 years 8 months ago
Using d-gap patterns for index compression
Sequential patterns of d-gaps exist pervasively in inverted lists of Web document collection indices due to the cluster property. In this paper the information of d-gap sequential...
Jinlin Chen, Terry Cook
SAC
2008
ACM
13 years 6 months ago
Discovering relationships among categories using misclassification information
Knowledge of relationships among categories is of the interest in different domains such as text classification, content analysis, and text mining. We propose and evaluate approac...
Saket S. R. Mengle, Nazli Goharian, Alana Platt
WWW
2006
ACM
14 years 8 months ago
Using symbolic objects to cluster web documents
Web Clustering is useful for several activities in the WWW, from automatically building web directories to improve retrieval performance. Nevertheless, due to the huge size of the...
Esteban Meneses, Oldemar Rodríguez-Rojas
CLEF
2009
Springer
13 years 5 months ago
Clustering for Text and Image-Based Photo Retrieval at CLEF 2009
For this year's Image CLEF Photo Retrieval task, we have prepared 5 submission runs to help us assess the effectiveness of 1) image content-based retrieval, and 2) textbased ...
Qian Zhu, Diana Inkpen