Abstract :
This paper deals with computational detection of humor. It assumes that computational humor is a useful task for any number of reasons and in many applications. It discusses the computational linguistic/ semantic precondi¬tions for computational humor and an ontological semantic approach to the task of humor detection, based on direct and comprehensive access to meaning rather than on trying to guess it through statistical-cum-syntactical keyword methods. The pa¬per is informed by the experience of designing and imple¬menting a humor detection model, whose decent success rate confirmed some of the assumptions while its misses made other ideas prominent, including the necessity of full text comprehension. The bulk of the paper explains how the comprehensive representation of meaning and, most impor¬tantly how unstructured natural language text is automati¬cally translated into the ontologically defined text meaning representations that can be used then to de¬tect humor in them, if any, automatically.
