Summarizing information by means of causal sentences through causal graphs

En este trabajo se aborda un método para obtener resúmenes de texto a través de sentencias causales. Para ello se definen las fases de extracción de sentencias causales de un conjunto de documentos, clasificación de las mismas para formar una base de conocimiento causal y la creación de un grafo causal a través de las sentencias obtenidas. Mediante el análisis de las conexiones causa-efecto del grafo, la eliminación de redundancia de conceptos que pueda existir y la determinación de los conceptos más relevantes (y que por tanto deberán aparecer en el resumen a obtener), somos capaces de presentar un resumen inductivo como respuesta a una pregunta lanzada sobre la base de conocimiento

The objective of this work is to propose a complete system able to extract causal sentences from a set of text documents, select the causal sentences contained, create a causal graph in base to a given concept using as source these causal sentences, and finally produce a text summary gathering all the information connected by means of this causal graph. This procedure has three main steps. The first one is focused in the extraction, filtering and selection of those causal sentences that could have relevant information for the system. The second one is focused on the composition of a suitable causal graph, removing redundant information and solving ambiguity problems. The third step is a procedure able to read the causal graph to compose a suitable answer to a proposed causal question by summarizing the information contained in it