Abstract
The Internet has brought unprecedented access to vast quantities of information. However, in recent times, the problem of information overload has become more and more marked, and we are now reaching a point where it is becoming increasingly difficult to locate the right information at the right time. One avenue of research that is set to improve information access, and relieve the information overload problem, is to develop technologies for automatically personalising information, both in terms of its content and mode of presentation. In this paper we describe the development of the PTV (Personalised Television Listings — http://www.ptv.ie system which tackles the information overload associated with modern TV listings data, by providing an Internet-based personalised listings service. PTV is capable of automatically compiling personalised guides to match the likes and dislikes of individual users.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Balabanovic M., Shoham Y. (1997) FAB: Content-Based Collaborative Recommender. Communications of the ACM, 40 (3) 66–72
Billsus, D. & Pazzani, M. J. (1998) Learning collaborative Information Filters. In, Proceedings of the International Conference on Machine Learning, Wisconsin, USA.
Goldberg D., Nichols D., Oki B. M., Terry D. (1992) Using Collaborative Filtering to Weave an Information Tapestry. Communications of the ACM, 35 (12) 61–70
Hammond, K. J., Burke, R., and Schmitt, K. (1996) A Case-Based Approach to Knowledge Navigation. In, (Leake, D.B, ed.) Case-Based Reasoning Experiences Lessons and Future Directions, MIT Press, 125–136
Jennings, A. & Higuchi, H. (1993) A user model neural network for a personal news service. User Modeling and User-Adapted Information, 3 (1). 1–25
Kay J. (1995) Vive la Difference! Individualised Interaction with Users. In: Proceedings IJCAI ‘85, Montréal, Canada, 978–984
Konstan J. A., Miller B. N., Maltz D., Herlocker J. L., Gordan L. R., Riedl J. (1997) Grouplens: Applying Collaborative Filtering to Usenet News. Communications of the ACM, 40 (3) 77–87
Maltz D., Ehrlich K. (1995) Pointing the Way: Active Collaborative Filtering. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’95) ACM Press, New York, N.Y., 202–209
Perkowitz, M. & Etzioni, O. (1997) Adaptive Web Sites: An AI Challenge. In, Proceedings of IJCAI-97, Nagoya, Japan.
Shardanand, U. & Maes, P.(1995) Social Information Filtering:Algorithms for Automating ‘Word of Mouth’. In, Proceedings of the Conference on Human Factors in Computing Systems (CHI95), ACM Press, New York, N.Y.. 210–217
Smyth, B. & Cotter, P. (1999) Surfing the Digital Wave: Generating Personalised TV Listings using Collaborative, Case-Based Recommendation. In, Proceedings of the International Conference on Case-Based Reasoning, Munich, Germany, 561–571
Watson, I. (1997) Applying Case-Based Reasoning: Techniques for Enterprise Systems, Morgan-Kaufmann.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag London
About this paper
Cite this paper
Smyth, B., Cotter, P. (2000). Sky’s the Limit. In: Ellis, R., Moulton, M., Coenen, F. (eds) Applications and Innovations in Intelligent Systems VII. Springer, London. https://doi.org/10.1007/978-1-4471-0465-0_1
Download citation
DOI: https://doi.org/10.1007/978-1-4471-0465-0_1
Publisher Name: Springer, London
Print ISBN: 978-1-85233-230-3
Online ISBN: 978-1-4471-0465-0
eBook Packages: Springer Book Archive