A Passage-Level Text Similarity Calculation

Abstract

Along with the explosion of web information, information flow service has attracted the attentions of users. In this kind of service, how to measure the similarity between texts and further filter the redundant information collected from multiple sources becomes the key solution to meet user’s desire. One text often mentions several events. The core event mostly decides the main content carried by the text. It should take the pivotal position. For this reason, this paper aims to construct a passage-level event connection graph to model the relations among the events mentioned by one text. The core event can be revealed and is further chosen to measure the similarity between two texts. As shown by experimental results, after measuring text similarity from a passage-level event representation perspective, our unsupervised measuring method acquires superior results than unsupervised methods by a large margin and even comparable results with some popular supervised neuron based methods.