This paper centers on the discussion of k-medoid-style clustering algorithms for supervised summary generation. This task requires clustering techniques that identify class-unifor...
In order to establish consolidated standards in novel data mining areas, newly proposed algorithms need to be evaluated thoroughly. Many publications compare a new proposition – ...
Search results clustering problem is defined as an automatic, on-line grouping of similar documents in a search hits list, returned from a search engine. In this paper we present t...
Clustering, or unsupervised classification, has many uses in fields that depend on grouping results from large amount of data, an example being the N-body cosmological simulation ...
We present a novel framework for the discovery and representation of general semantic relationships that hold between lexical items. We propose that each such relationship can be ...