The REG Summarization System with Question Reformulation at QA@INEX Track 2010

摘要

In this paper we present REG, a graph approach to study a fundamental problem of Natural Language Processing: the automatic summarization of documents. The algorithm models a document as a graph, to obtain weighted sentences. We applied this approach to the INEXQQA 2010 task (question-answering). To do it, we have extracted the terms and name entities from the queries, in order to obtain a list of terms and name entities related with the main topic of the question. Using this strategy, REG obtained good results regarding performance (measured with the automatic evaluation system FRESA) and readability (measured with human evaluation), being one of the seven best systems into the task.