Dialog Summarization using Phrase Structure Analysis and Text Clustering

Abstract

Contact centers have massive amount of dialog records to be used to improve the quality of their service. This paper describes a method of summarizing a large number of dialogs on the same topic into a tree structure. The method consists of two steps: 1) summarization of each dialog with phrase structure rules, and 2) organizing dialogs into a tree structure using text clustering. A common oddness was observed among summarized dialogs, and this problem was mitigated by applying Multi-Sequence Alignment (MSA). With the proposed method, we were able to summarize real-life dialogs into a reasonably small tree with only two hours of rule writing labor. Also, applying MSA helped to reduce the number of nodes and led to a higher purity score.