Paper: Automatic Identification of Important Segments and Expressions for Mining of Business-Oriented Conversations at Contact Centers

ACL ID D07-1048
Title Automatic Identification of Important Segments and Expressions for Mining of Business-Oriented Conversations at Contact Centers
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

Textual records of business-oriented conver- sations between customers and agents need to be analyzed properly to acquire useful business insights that improve productivity. For such an analysis, it is critical to iden- tify appropriate textual segments and ex- pressions to focus on, especially when the textual data consists of complete transcripts, which are often lengthy and redundant. In this paper, we propose a method to iden- tify important segments from the conversa- tions by looking for changes in the accuracy of a categorizer designed to separate differ- ent business outcomes. We extract effective expressions from the important segments to define various viewpoints. In text mining a viewpoint defines the important associations between key entities and it is crucial that the correct...