Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
Current Data Mining techniques usually do not have a mechanism to automatically infer semantic features inherent in the data being “mined”. The semantics are either injected i...
Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
Word sense disambiguation for unrestricted text is one of the most difficult tasks in the fields of computational linguistics. The crux of the problem is to discover a model that ...
Finding information is a problem shared by people and intelligent systems. This paper describes an experiment combining both human and machine aspects in a knowledgebased system t...