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» Discriminative K-means for Clustering
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PRL
2010
158views more  PRL 2010»
13 years 6 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
CIS
2005
Springer
14 years 1 months ago
Concept Chain Based Text Clustering
Different from familiar clustering objects, text documents have sparse data spaces. A common way of representing a document is as a bag of its component words, but the semantic re...
Shaoxu Song, Jian Zhang, Chunping Li
HT
2000
ACM
13 years 12 months ago
Clustering hypertext with applications to web searching
Clustering separates unrelated documents and groups related documents, and is useful for discrimination, disambiguation, summarization, organization, and navigation of unstructure...
Dharmendra S. Modha, W. Scott Spangler
ESWA
2008
213views more  ESWA 2008»
13 years 7 months ago
Visualization of patent analysis for emerging technology
Many methods have been developed to recognize those progresses of technologies, and one of them is to analyze patent information. And visualization methods are considered to be pr...
Young Gil Kim, Jong Hwan Suh, Sang-Chan Park
TOG
2012
280views Communications» more  TOG 2012»
11 years 10 months ago
What makes Paris look like Paris?
Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain g...
Carl Doersch, Saurabh Singh, Abhinav Gupta, Josef ...