Paper: Opinion Summarization with Integer Linear Programming Formulation for Sentence Extraction and Ordering

ACL ID C10-2105
Title Opinion Summarization with Integer Linear Programming Formulation for Sentence Extraction and Ordering
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

In this paper we propose a novel algorithm for opinion summarization that takes ac- count of content and coherence, simulta- neously. We consider a summary as a se- quence of sentences and directly acquire the optimum sequence from multiple re- view documents by extracting and order- ing the sentences. We achieve this with a novel Integer Linear Programming (ILP) formulation. Our proposed formulation is a powerful mixture of the Maximum Cov- erage Problem and the Traveling Sales- man Problem, and is widely applicable to text generation and summarization tasks. We score each candidate sequence accord- ing to its content and coherence. Since our research goal is to summarize reviews, the content score is defined by opinions and the coherence score is developed in training against the review ...