Abstract
We describe Order-Based Retrieval, which is an approach to case retrieval based on the application of partial orders to the case base. We argue that it is well-suited to product recommender applications because, as well as retrieving products that best match customer-specified ‘ideal’ attribute-values, it also: allows the customer to specify soft constraints; gives a natural semantics and implementation to tweaks; and delivers an inherently diverse result set.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bradley, K. & B. Smyth: Improving Recommendation Diversity, In D. O’Donoghue (ed.), Procs. of the Twelfth Irish Conference on Artificial Intelligence and Cognitive Science, pp. 85–94, 2001.
Bridge, D.: Product Recommendation Systems: A New Direction, In R. Weber & C.G. von Wangenheim (eds.), Procs. of the Workshop Programme at the Fourth International Conference on Case-Based Reasoning, pp. 79–86, 2001.
Bridge, D. & A. Ferguson: An Expressive Query Language for Product Recommender Systems, Artificial Intelligence Review, to appear, 2002.
Ferguson, A. & Bridge, D.G.: Partial Orders and Indifference Relations: Being Purposefully Vague in Case-Based Retrieval, in Blanzieri, E. & Portinale, L. (eds.), Advances in Case-Based Reasoning (Procs. of the 5th European Workshop on Case-Based Reasoning), LNAI 1898, pp. 74–85, Springer, 2000
Ferguson, A. & D. Bridge: Weight Intervals: Conservatively adding quantified uncertainty to similarity, In D. O’Donoghue (ed.), Procs. of the Twelfth Irish Conference on Artificial Intelligence & Cognitive Science, pp. 75–84, 2001.
Hammond, K.J., R. Burke & K. Schmitt: Case Based Approach to Knowledge Navigation, In D.B. Leake (ed.), Case-Based Reasoning-Experiences, Lessons and Future Directions, pp. 125–136, MIT Press, 1996.
Osborne, H.R. & D.G. Bridge: A Case Base Similarity Framework, In I. Smith & B. Faltings (eds.), Advances in Case-Based Reasoning (Procs. of the Third European Workshop on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 1168, pp. 309–323, Springer, 1996.
Smyth, B. & P. Cotter: Surfing the Digital Wave: Generating Personalised TV Listings Using Collaborative, Case-Based Recommendation, In K.D. Althoff, R. Bergmann & L.K. Branting (eds.), Case-Based Reasoning Research and Development (Procs. of the Third International Conference on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 1650, pp. 5612–571, Springer, 1999.
Smyth, B. & P. McClave: Similarity vs. Diversity, In D.W. Aha & I. Watson (eds.), Case-Based Reasoning Research and Development (Procs. of the Fourth International Conference on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 2080, pp. 347–361, Springer, 2001.
Vollrath, I., W. Wilke & R. Bergmann: Case-Based Reasoning Support for Online Catalog Sales, IEEE Internet Computing, vol. 2(4), pp. 45–54, 1998.
Wilke, W., M. Lenz & S. Wess: Intelligent Sales Support with CBR, In Lenz, M., B. Bartsch-Spörl, H.-D. Burkhard & S. Wess (eds), Case-Based Reasoning Technology: From Foundations to Applications, Lecture Notes in Artificial Intelligence 1400, pp. 91–113 Springer, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bridge, D., Ferguson, A. (2002). Diverse Product Recommendations Using an Expressive Language for Case Retrieval. In: Craw, S., Preece, A. (eds) Advances in Case-Based Reasoning. ECCBR 2002. Lecture Notes in Computer Science(), vol 2416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46119-1_5
Download citation
DOI: https://doi.org/10.1007/3-540-46119-1_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44109-0
Online ISBN: 978-3-540-46119-7
eBook Packages: Springer Book Archive