Weighted Abduction for Discourse Processing Based on Integer Linear Programming
Naoya Inouea, Ekaterina Ovchinnikovab, Kentaro Inuia and Jerry Hobbsb, aTohoku University, Sendai, Japan, bUSC/ISI, Marina del Rey, CA, USA
Abstract
This chapter explores the logical framework called weighted abduction as applied to solving discourse-processing tasks. Weighted abduction incorporates a cost propagation mechanism allowing us to estimate the likelihood of the obtained abductive proofs. We use a tractable implementation of weighted abduction based on Integer Linear Programming and a large knowledge base generated automatically. We first perform an experiment on plan recognition using the dataset originally developed for Ng and Mooney’s ...
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