Abstract
The search for an online product that matches e-shoppers’ needs and preferences can be frustrating and time-consuming. Browsing large lists arranged in tree-like structures demands focused attention from e-shoppers. Keyword search often results in either too many useless items (low precision) or few or none useful ones (low recall). This can cause potential buyers to seek another seller or choose to go in person to a store. This paper introduces the SPOT (Stated Preference Ontology Targeted) methodology to model e-shoppers’ decision-making processes and use them to refine a search and show products and services that meet their preferences. SPOT combines probabilistic theory on discrete choices, the theory of stated preferences, and knowledge modeling (i.e. ontologies). The probabilistic theory on discrete choices coupled with e-shoppers’ stated preferences data allow us to unveil parameters e-shoppers would employ to reach a decision of choice related to a given product or service. Those parameters are used to rebuild the decision process and evaluate alternatives to select candidate products that are more likely to match e-shoppers’ choices. We use a synthetic example to demonstrate how our approach distinguishes from currently used methods for e-commerce.
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
Ardissono, L., Godoy, A.: Tailoring the Interaction with Users in Web Stores. User Modeling and User-Adapted Interaction 10, 251–303 (2000)
Ben-Akiva, M., Lerman, R.: Discrete Choice Analysis. MIT Press, Cambridge (1985)
Burke, R.: Knowledge-Based Recommender Systems. In: Kent, A. (ed.) Encyclopedia of Library and Information Systems, 69, 32, Marcel Dekker, New York (2000)
Burke, R.: Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction 12(4), 331–370 (2002)
Cotter, P., Smyth, B.: PTV: Intelligent Personalised TV Guides. In: Proceedings of Innovative Applications of Artificial Intelligence, pp. 957–964. AAAI Press/The MIT, Stanford, California, USA (2000)
Carvalho, M, D.: A Comparison of Neural Networks and Econometric Discrete Choice Models in Transport. Institute for Transport Studies, University of Leeds, UK (PhD-thesis) (1998)
Domingue, J., Martins, M., Tan, J., Stutt, A., Pertusson, H.: Alice: Assiting Online Shoppers through Ontologies and Novel Interface Metaphors. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 335–351. Springer, Heidelberg (2002)
Fowkes, T., Shinghal, N.: The Leeds Adaptive Stated Preference Methodology (In Danielis, R. (ed.) Freight Transport Demand and Stated Preference Experiments, F. Angeli, Milan) (2002)
Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)
Kocur, G., Adler, T., Hyman, W., Aunet, B.: Guide to Forecasting Travel Demand with Direct Utility Assessment. Report No. UMTA-NH-11-0001-82, Urban Mass Transportation Administration, US Department of Transportation, Washington, DC (1982)
Kozinets, R.V.: E-Tribalized Marketing: the Strategic Implications of Virtual Communities of Consumption. European Management Journal 17(3), 252–264 (1999)
Luce, R.D.: Individual Choice Behavior, New York. John Wiley & Sons, West Sussex, England (1959)
Louviere, J.J.: Analyzing Decision Making: Metric Conjoint Analysis. Sage Publications, Newbury Park, CA (1988)
McGinty, L., Smyth, B.: Comparison-Based Recommendation. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 575–589. Springer, Heidelberg (2002)
Pearmain, D., Kroes, E.: Stated Preference Techniques: a Guide to Practice. Steer Davies & Gleave, UK (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Martins, M.C., Weber, R. (2007). Modeling Preferences Online. In: Filipe, J., Cordeiro, J., Pedrosa, V. (eds) Web Information Systems and Technologies. Lecture Notes in Business Information Processing, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74063-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-74063-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74062-9
Online ISBN: 978-3-540-74063-6
eBook Packages: Computer ScienceComputer Science (R0)