Building and Applying Profiles Through Term Extraction

This paper proposes a technique to build entity profiles starting from a set of defining corpora, i.e., a corpus considered as the definition of each entity. The proposed technique is applied in a classification task in order to determine how much a text, or corpus, is related to each of the profiled entities. This technique is general enough to be applied to any kind of entity, however, this paper experiments are conduct over entities describing a set of professors of a computer science graduate school through their advised M.Sc. thesis and Ph.D. dissertations. The profiles of each entity are applied to categorize other texts into one of the builded profiles. The analysis of the obtained results illustrates the power of the proposed technique.