Proceedings of the 13th international conference on World Wide Web
Automatic analysis of call-center conversations
Proceedings of the 14th ACM international conference on Information and knowledge management
Mining Ontological Knowledge from Domain-Specific Text Documents
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Automatic call section segmentation for contact-center calls
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Semi-automated logging of contact center telephone calls
Proceedings of the 17th ACM conference on Information and knowledge management
Identification of class specific discourse patterns
Proceedings of the 17th ACM conference on Information and knowledge management
Getting insights from the voices of customers: Conversation mining at a contact center
Information Sciences: an International Journal
A survey of types of text noise and techniques to handle noisy text
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
Automatic agenda graph construction from human-human dialogs using clustering method
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
An empirical study of corpus-based response automation methods for an e-mail-based help-desk domain
Computational Linguistics
Hybrid approach to robust dialog management using agenda and dialog examples
Computer Speech and Language
Customer-focused service management for contact centers
IBM Journal of Research and Development
Automatically generating term-frequency-induced taxonomies
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
The effect of noise in automatic text classification
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Mining automatic speech transcripts for the retrieval of problematic calls
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
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Call centers handle customer queries from various domains such as computer sales and support, mobile phones, car rental, etc. Each such domain generally has a domain model which is essential to handle customer complaints. These models contain common problem categories, typical customer issues and their solutions, greeting styles. Currently these models are manually created over time. Towards this, we propose an unsupervised technique to generate domain models automatically from call transcriptions. We use a state of the art Automatic Speech Recognition system to transcribe the calls between agents and customers, which still results in high word error rates (40%) and show that even from these noisy transcriptions of calls we can automatically build a domain model. The domain model is comprised of primarily a topic taxonomy where every node is characterized by topic(s), typical Questions-Answers (Q&As), typical actions and call statistics. We show how such a domain model can be used for topic identification of unseen calls. We also propose applications for aiding agents while handling calls and for agent monitoring based on the domain model.