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» Using Clustering Methods for Discovering Event Structures
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TMM
2010
181views Management» more  TMM 2010»
14 years 10 months ago
Mining Group Nonverbal Conversational Patterns Using Probabilistic Topic Models
Abstract--The automatic discovery of group conversational behavior is a relevant problem in social computing. In this paper, we present an approach to address this problem by defin...
Dinesh Babu Jayagopi, Daniel Gatica-Perez
150
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SSDBM
2006
IEEE
123views Database» more  SSDBM 2006»
15 years 9 months ago
Mining Hierarchies of Correlation Clusters
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...
Elke Achtert, Christian Böhm, Peer Kröge...
ACL
2003
15 years 5 months ago
Unsupervised Learning of Dependency Structure for Language Modeling
This paper presents a dependency language model (DLM) that captures linguistic constraints via a dependency structure, i.e., a set of probabilistic dependencies that express the r...
Jianfeng Gao, Hisami Suzuki
CSREAEEE
2006
154views Business» more  CSREAEEE 2006»
15 years 5 months ago
Structural Discovery of E-lessons
An e-lesson is comprised of a "body" and a "view". The body is the actual content of the e-lesson and the assumption is that it is an html document. The view i...
Azita Bahrami
ICPP
2000
IEEE
15 years 8 months ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary