Applying Logic Forms and Statistical Methods to CL-SR Performance

This paper describes in detail the combination of NLP methods applied to the treatment of logic forms in the topic processing and statistical methods applied to the search engine in the frame of the CL-SR performance. The method that infers the logic form of a topic is based on dependency analysis between the words of the topic. These dependencies between the words of the topic are calculated using the MINIPAR parser. Different combinations of the topic, description and narrative fields are used in the runs to perform the retrieval process. The based on logic forms method processes the description and narrative fields of the topics. This processing task consists on the removal of several terms according to the logic structure of the processed field in the logic form. On the other hand, the statistical processing applied to the search engine consists on using IR-n system. IR-n system is a passage retrieval system that manages overlapping of variable passages that are composed by a number of sentences. Different statistical similarity measures are managed by IR-n system to acquire the topic terms weight. The removal of several topic terms according to the logic structure of the topic origines that the rest of the topic terms acquire a better relevance.