User modelling for live help systems: initial results

ABSTRACT

This paper explores the role of user modelling in live help systems for e-commerce web sites. There are several potential benefits with user modelling in this context: 1) Human assistants can use the personal information in the user models to provide the users with efficient support tailored to their personal needs; 2) Assistants can be more comfortable in their supporting role; 3) Consultation resources can be saved, and thus, financial savings can be made for the e-commerce company. A user modelling approach has been implemented and deployed in a real web environment as part of a live help system. Following the deployment we have analysed consultation dialogue logs and answers to a questionnaire for participating assistants. The initial results show that assistants consider user modelling to be helpful and that consultation dialogues can be an important source for user model data collection.

REFERENCES

• 1: J. Aberg and N. Shahmehri. The role of human Web assistants in e-commerce: an analysis and a usability study. Internet Research: Electronic Networking Applications and Policy, 10(2):114-125, 2000.
• 2: J. Aberg , N. Shahmehri, Collection and Exploitation of Expert Knowledge in Web Assistant Systems, Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 7, p.7057, January 03-06, 2001
• 3: Johan Aberg , Nahid Shahmehri, An empirical study of human Web assistants: implications for user support in Web information systems, Proceedings of the SIGCHI conference on Human factors in computing systems, p.404-411, March 2001, Seattle, Washington, United States [doi>10.1145/365024.365305]
• 4: H. G. Bernett and A. Gharakhanian. Call Center Evolution: Computer Telephone Integration and Web Integration. The Telecommunications Review, MitreTek Systems, pages 107-114, 1999.
• 5: S. Elzer, J. Chu-Carrol, and S. Carberry. Recognizing and Utilizing User Preferences in Collaborative Consultation Dialogues. In Proceedings of the Fourth International Conference onUser Modeling, pages 19-24, 1994.
• 6: M. Fridgen, J. Schackman, and S. Volkert. Preference Based Customer Models for Electronic Banking. In Proceedings of the 8th European Conference on Information Systems, pages 789-795, Vienna, Austria, 2000.
• 7: S. L. Jarvenpaa and P. A.Todd. Consumer Reactions to Electronic Shopping on the World Wide Web. International Journal of Electronic Commerce, 1(2):59-88, 1997.
• 8: Robert Kass , Tim Finin, Modeling the user in natural language systems, Computational Linguistics, v.14 n.3, September 1988
• 9: L. R. Vijaysarathy and J. M. Jones. Print and Internet catalog shopping. Internet Research: Electronic Networking Applications and Policy, 10(3):191-202, 2000.
• 10: Alfred Kobsa , Wolfgang Wahlster, User models in dialog systems, Springer-Verlag New York, Inc., New York, NY, 1990

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: User-centered design

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Training, help, and documentation

  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.4 Electronic Commerce

General Terms:
Human Factors, Performance, Theory