Learning a probabilistic model of event sequences from Internet weblog stories
Mehdi Manshadi
U. Rochester
Date: Thursday, August 23, 2007
Time: 2:00 PM - 3:00 PM
Location: 6th floor amphitheater
Host:
Internet weblogs provide a huge source of stories that can be used as a large corpus to learn statistical regularities of narrative text. In this talk, I will describe an approach for building a statistical model of sequences of narrative events that can be used in many different applications, including event prediction, automatic story generation, and story coherence evaluation. In this model, we represent events described in narrative text sentences as a predicate (main verb) with a single argument. We use language modeling techniques to find the probabilities of sequences of events in a story. We will describe the results of some experiments to show how well this model captures the structure of event sequences in narrative text.