Approaches to intelligent information retrieval
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Using IR techniques for text classification in document analysis
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Information Processing and Management: an International Journal
An extended vector-processing scheme for searching information in hypertext systems
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal - Special issue on Information Seeking In Context (ISIC)
Adapting a diagnostic problem-solving model to information retrieval
Information Processing and Management: an International Journal
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
WISE: A World Wide Web Resource Database System
IEEE Transactions on Knowledge and Data Engineering
Centralization as a design consideration for the management of call centers
Information and Management
Quantum symmetrically-private information retrieval
Information Processing Letters
Information Processing and Management: an International Journal - Special issue: Cross-language information retrieval
Collaborative information retrieval in an information-intensive domain
Information Processing and Management: an International Journal
An enhanced genetic approach to optimizing auto-reply accuracy of an e-learning system
Computers & Education
Multi-agent Framework Support for Adaptive e-Learning
ICWL '08 Proceedings of the 7th international conference on Advances in Web Based Learning
Expert Systems with Applications: An International Journal
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Most existing network-based customer services heavily rely on manpower in replying e-mails or on-line requests from customers, which not only increases the service cost, but also delay the time for responding the service requests. To cope with these problems, this paper proposes a customer service system, which can automatically handle customer requests by analyzing the contents of the requests and finding the most feasible answers from the frequently asked question (FAQ) database. In the situation that a customer is not satisfied with the reply, the system will forward the request to the appropriate service personnel for further processing. An assistance mechanism has been developed to help the service personnel in finding potential answers from existing FAQ data or creating more appropriate answers. Experimental results on practical applications showed that over 87.3% of users were satisfied with the replies given by the system; therefore, we conclude that the system can significantly reduce the service cost and provide more efficient and effective customer service.