Modelo de reconhecimento de vinculação textual baseado em regras linguísticas e informações morfossintáticas voltado para ambientes virtuais de ensino e aprendizagem - Flores, Evandro Metz (Universidade do Vale do Rio dos Sinos, 2014)
The fast evolution of information and communication technologies has enabled the development of modalities of teaching and learning, such as distance education, that allow to reach people previously unable to attend higher education. An important aspect of these modalities is the extensive use of digital mediation resources. These resources can generate a large volume of data that sometimes is not feasible for beneficial manual use by the teachers involved in this interaction. In this context there is a necessity and opportunity for defining tools and approaches that can act to automate part of this work. One of these possibilities is the verification of textual responses correctness, where the goal is to identify linkages between textual samples, which can be, for example, different textual answer to a question. Although presenting good results, techniques currently applied to this problem have deficiencies or characteristics that decrease their accuracy or suitability in several contexts. Few studies are able to perform textual entailment in case the verbal inflection was changed; others are not able to identify important information or position in the sentence where the information is found. Moreover, few works are adapted to Portuguese. This work proposes a model to recognition of textual entailment based on linguistic rules, which seeks to overcome these problems by presenting a new approach through the combined use of syntactic analysis, morphology, linguistic rules, detection of the bending voice, treatment of denial and the use of synonyms. This work also presents a prototype developed to evaluate the model proposed herein. The end results, which are promising, allow the identification of textual linking of different textual samples accurately and with flexibility.
Keywords: Big data; Processamento de linguagem natural; Perguntas e respostas; Regras linguísticas; Reconhecimento de vinculação textual; Natural language processing; Question and answering; Linguistic rules; Recognising textual entailment; ACCNPQ::Ciências Exatas e da Terra::Ciência da Computação