We develop a revealed-preferencetheory for multiple agents. Some features of our construction, which draws heavily on Jeffrey's utility theory and on formal constructions by D...
The selection of features for classification, clustering and approximation is an important task in pattern recognition, data mining and soft computing. For real-valued features, th...
Text clustering is potentially very useful for exploration of text sets that are too large to study manually. The success of such a tool depends on whether the results can be expl...
We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
The performance of document clustering systems depends on employing optimal text representations, which are not only difficult to determine beforehand, but also may vary from one ...