This paper presents a new unsupervised approach to generating ultra-concise summaries of opinions. We formulate the problem of generating such a micropinion summary as an optimization problem, where we seek a set of concise and non-redundant phrases that are readable and represent key opinions in text. We measure representativeness based on a modifi ed mutual information function and model readability with an n-gram language model. We propose some heuristic algorithms to efficiently solve this optimization problem.
- Opinion Driven Decision Support System
- FindiLike: A Preference Driven Entity Search Engine for Evaluating Entity Retrieval and Opinion Summarization
- Micropinion Generation: An Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions
- FindiLike: Opinion-Driven Hotel Search
- Opinion-Based Entity Ranking