9:20 AM - 9:40 AM
[2K1-02] Dialog Summarization using Phrase Structure Analysis and Text Clustering
Keywords:Dialog, Summarization, Text clustering
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.
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.