Using Latent Semantic Indexing as a metric for evaluating research potentialities through Innovation Public Policies

Abstract

Public innovation policies usually define strategies for Public research organizations, such as universities, in order to guide the next research projects of such organizations. Sometimes, it is difficult to know the actual state of an organization when a new policy is released by the government. The objective of this paper is to present the application of Latent Semantic Analysis, a technique of information retrieval, in order to create an index and automatically classify research projects, using text fields like title and abstract, to areas and subareas defined by related terms. It is also proposed a case study of about 200 projects from five graduate programs of the Universidade Federal do Tocantins. The proposed solution was capable of satisfactorily classify each project to the areas and subareas of a recent policy from the Science, Technology, Innovations, and Communications Ministry. In this way, the university could have some decision-making information, and the results could sustain for which internal policies could be implemented to maximize its actuation faced to the national innovation policy.