This work presents a new algorithm, called Heuristically Accelerated Q–Learning (HAQL), that allows the use of heuristics to speed up the well-known Reinforcement Learning algori...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
This work explores the application of clustering methods for grouping structurally similar XML documents. Modeling the XML documents as rooted ordered labeled trees, we apply clust...
Theodore Dalamagas, Tao Cheng, Klaas-Jan Winkel, T...
This paper presents a novel method for wide coverage parsing using an incremental strategy, which is psycholinguistically motivated. A recursive neural network is trained on treeba...
Fabrizio Costa, Vincenzo Lombardo, Paolo Frasconi,...
This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW...
Eneko Agirre, Olatz Ansa, Eduard H. Hovy, David Ma...
Abstract. This paper explores potential improvements to Zhang’s personalized trust approach for e-commerce, in particular examining means of optimizing the number of advisors tha...