This paper addresses the automatic analysis of court-net sports video content. We extract information about the players, the playing-field in a bottom-up way until we reach scene-l...
Traditional vector-based models use word co-occurrence counts from large corpora to represent lexical meaning. In this paper we present a novel approach for constructing semantic ...
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. These semantic concepts do not exist in isolatio...
When a user cannot find a word, he may think of semantically related words that could be used into an automatic process to help him. This paper presents an evaluation of lexical r...
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...