Granular computing is gradually changing from a label to a new field of study. The driving forces, the major schools of thought, and the future research directions on granular co...
We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes super...
Peter L. Bartlett, Michael Collins, Benjamin Taska...
We investigate the use of clustering methods for the task of grouping the text spans in a news article that refer to the same event. We provide evidence that the order in which eve...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
We provide empirical support for the assertions that high level of knowledge construction is associated with structured design and that knowledge construction is associated with c...
Structured peer-to-peer (p2p) overlay networks provide a decentralized, self-organizing substrate for distributed applicad support powerful abstractions such as distributed hash t...
Large-scale information integration, and in particular, search on the World Wide Web, is pushing the limits on the combination of structured data and unstructured data. By its ver...
We present discrete stochastic mathematical models for the growth curves of synchronous and asynchronous evolutionary algorithms with populations structured according to a random ...
Mario Giacobini, Marco Tomassini, Andrea Tettamanz...
XML information retrieval (XML-IR) systems aim to provide users with highly exhaustive and highly specific results. To interact with XML-IR systems, users must express both their ...
While the Semantic Web requires a large amount of structured knowledge (triples) to allow machine reasoning, the acquisition of this knowledge still represents an open issue. Indee...