Dialogue-Oriented Review Summary Generation for Spoken Dialogue Recommendation Systems

In this paper we present an opinion summarization technique in spoken dialogue systems. Opinion mining has been well studied for years, but very few have considered its application in spoken dialogue systems. Review summarization, when applied to real dialogue systems, is much more complicated than pure text-based summarization. We conduct a systematic study on dialogue-system-oriented review analysis and propose a three-level framework for a recommendation dialogue system. In previous work we have explored a linguistic parsing approach to phrase extraction from reviews. In this paper we will describe an approach using statistical models such as decision trees and SVMs to select the most representative phrases from the extracted phrase set. We will also explain how to generate informative yet concise review summaries for dialogue purposes. Experimental results in the restaurant domain show that the proposed approach using decision tree algorithms achieves an outperformance of 13% comp...

• Type: Journal
• Year: 2010
• Where: NAACL
• Authors: Jingjing Liu, Stephanie Seneff, Victor Zue
• Keywords: Computational Linguistics, Decision Tree, Dialogue System, NAACL 2010, Opinion Summarization Technique