Pair-Wise Cluster Analysis

Details Pair-Wise Cluster Analysis Pair-Wise Cluster Analysis

2010-09-19

arxiv.org/abs/1009.3601v1

Statistics

Machine Learning

Scientific paper

This paper studies the problem of learning clusters which are consistently present in different (continuously valued) representations of observed data. Our setup differs slightly from the standard approach of (co-) clustering as we use the fact that some form of `labeling' becomes available in this setup: a cluster is only interesting if it has a counterpart in the alternative representation. The contribution of this paper is twofold: (i) the problem setting is explored and an analysis in terms of the PAC-Bayesian theorem is presented, (ii) a practical kernel-based algorithm is derived exploiting the inherent relation to Canonical Correlation Analysis (CCA), as well as its extension to multiple views. A content based information retrieval (CBIR) case study is presented on the multi-lingual aligned Europal document dataset which supports the above findings.

Affiliated with

Also associated with

No associations

Rating

Pair-Wise Cluster Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Pair-Wise Cluster Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Pair-Wise Cluster Analysis will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-408604