Conference paper
Modeling Preferences Online
Web Information Systems and Technologies, v 1
01 Jan 2007
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.
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Details
- Title
- Modeling Preferences Online
- Creators
- Maria Cleci Martins - Universidade Luterana do BrasilRosina Weber - Drexel University, College of Information Science and Technology (1995-2013)
- Contributors
- Joaquim Filipe (Editor) - Instituto Politecnico de SetubalJosé Cordeiro (Editor) - Instituto Politecnico de SetubalVitor Pedrosa (Editor) - Instituto Para Os Sistemas e Tecnologias de Informação Controlo e Comunicação
- Publication Details
- Web Information Systems and Technologies, v 1
- Conference
- International Conferences WEBIST 2005 and WEBIST 2006 (Miami, Florida, United States and Setúbal, Portugal, 26 May 2005–28 May 2005)
- Series
- Lecture Notes in Business Information Processing; 1
- Publisher
- Springer Nature
- Number of pages
- 2
- Resource Type
- Conference paper
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000250712700012
- Other Identifier
- 991019170560804721
InCites Highlights
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- Collaboration types
- International collaboration
- Web of Science research areas
- Business
- Computer Science, Information Systems
- Computer Science, Theory & Methods
- Information Science & Library Science