Abstract
Unsupervised classification is used to identify similar entities in a dataset and is extensively used in many application domains such as spam filtering [5], medical diagnosis [15], demographic research [13], etc. Unsupervised classification using K-Means generally clusters data based on (1) distance-based attributes of the dataset [4, 16, 17, 23] or (2) combinatorial properties of a weighted graph representation of the dataset [8].
Original language | English (US) |
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Title of host publication | Graph Embedding for Pattern Analysis |
Publisher | Springer New York |
Pages | 119-138 |
Number of pages | 20 |
ISBN (Electronic) | 9781461444572 |
ISBN (Print) | 9781461444565 |
DOIs | |
State | Published - Jan 1 2013 |
ASJC Scopus subject areas
- Engineering(all)