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Text Mining of Business-Oriented Conversations at a Call Center

  • Hironori Takeuchi
  • Takahira Yamaguchi
Chapter
Part of the Studies in Big Data book series (SBD, volume 3)

Abstract

Recently textual record of the telephone conversation at the contact center can be transcribed by the automatic speech recognition technology. In this research, we extend the text mining system for the call summary records and construct a conversation mining system for the business-oriented conversation at the contact center. To acquire useful business insights from the conversation data through the text mining system, it is critical to identify appropriate textual segments and expressions as viewpoints to focus on. In the analysis of call summary data using a text mining system, some experts defined the viewpoints for the analysis by looking some sample records and prepared the dictionaries based on frequent keywords in the sample dataset. It is however difficult to identify such viewpoints manually in advance because the target data is consists of complete transcripts that are often lengthy and redundant. In this research, we define the model of the business-oriented conversations and propose a mining method to identify segments that make impact on the outcome of the conversation and extract useful expressions in each identified segments. In the experiment, we process the real datasets from a car rental service center and construct a mining system. Through the system, we show the effectiveness of the method based on the defined conversation model.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Graduate School of Science and TechnologyKeio UniversityKanagawaJapan
  2. 2.IBM Research - TokyoIBM Japan, Ltd.TokyoJapan

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