Clustering belief functions based on attracting and conflicting metalevel evidence

Details Clustering belief functions based on attracting and conflicting metalevel evidence Clustering belief functions based on attracting and conflicting metalevel evidence

2003-05-16

arxiv.org/abs/cs/0305031v1

in Proceedings of the Ninth International Conference on Information Processing and Management of Uncertainty in Knowledge-base

Computer Science

Artificial Intelligence

8 pages, 3 figures

Scientific paper

In this paper we develop a method for clustering belief functions based on attracting and conflicting metalevel evidence. Such clustering is done when the belief functions concern multiple events, and all belief functions are mixed up. The clustering process is used as the means for separating the belief functions into subsets that should be handled independently. While the conflicting metalevel evidence is generated internally from pairwise conflicts of all belief functions, the attracting metalevel evidence is assumed given by some external source.

Affiliated with

Also associated with

No associations

Rating

Clustering belief functions based on attracting and conflicting metalevel evidence 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 Clustering belief functions based on attracting and conflicting metalevel evidence, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Clustering belief functions based on attracting and conflicting metalevel evidence will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-545311