In this paper, we describe ontology-based text categorization in which the domain ontologies are automatically acquired through morphological rules and statistical methods. The on...
Abstract. Evaluation is one of the hardest tasks in automatic text summarization. It is perhaps even harder to determine how much a particular component of a summarization system c...
Abstract. This paper proposes a new knowledge-based method for clustering metagenome short reads. The method incorporates biological knowledge in the clustering process, by means o...
Gianluigi Folino, Fabio Gori, Mike S. M. Jetten, E...
Human-quality text summarization systems are di cult to design, and even more di cult to evaluate, in part because documents can di er along several dimensions, such as length, wri...
Jade Goldstein, Mark Kantrowitz, Vibhu O. Mittal, ...
In supervised kernel methods, it has been observed that the performance of the SVM classifier is poor in cases where the diagonal entries of the Gram matrix are large relative to ...