Textual data mining of service center call records
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Message classification in the call center
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Hybrid Context Model Based on Multilevel Situation Theory and Ontology for Contact Centers
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
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One of the important challenges in today's contact center solutions is to increase the speed at which the agents can find information to respond to customer queries. In this paper, we study the issues relevant to information retrieval by contact center agents and propose a solution to address those issues. Our proposed solution is towards: (a) defining user specific, agent specific, and business specific contexts for contact center; (b) using simple mechanisms initially to derive current context of a query and pre-fetch the information and appropriately present the pre-fetched information to the agent; (c) derive contact center specific analyzed context based on past information about customer, agent and business scenarios to understand the context of the query; and (d) using the current and analyzed contexts to retrieve information.