We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
The ability to extract meaningful fragments from an ontology is key for ontology re-use. We propose a definition of a module that guarantees to completely capture the meaning of a...
Bernardo Cuenca Grau, Ian Horrocks, Yevgeny Kazako...
While many works have been devoted to service matchmaking and modeling nonfunctional properties, the problem of matching service requests to offers in an optimal way has not yet b...
We consider information-theoretic key agreement between two parties sharing somewhat different versions of a secret w that has relatively little entropy. Such key agreement, also ...
Transactional data are ubiquitous. Several methods, including frequent itemsets mining and co-clustering, have been proposed to analyze transactional databases. In this work, we p...
Yang Xiang, Ruoming Jin, David Fuhry, Feodor F. Dr...