Cited By
View all- Endres MKastner JRudenko L(2018)Analyzing and Clustering Pareto-Optimal Objects in Data StreamsLearning from Data Streams in Evolving Environments10.1007/978-3-319-89803-2_4(63-91)Online publication date: 29-Jul-2018
Advanced preference query processing for e-commerce
Pages 1457 - 1462
Abstract
Travel and tourism represents the leading domain for applications in b2c e-commerce. Thus, it deserves highest attention. Due to insufficient search engines, however, arranging a trip on current online travel portals is often not as easy as it seems. We present a novel approach for an advanced processing of database queries dealing with individual as well as global preferences of customers. Our approach also comprises the deployment of existing preference search technology to the tourism domain of electronic commerce. Consequently, the tedious empty-result-effect is avoided. Thereby, a novel, personalized search process delivering custom-tailored products is enabled for tourism and in general for e-commerce, respectively. A first prototype implementing our advanced search has shown promising results.
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Index Terms
- Advanced preference query processing for e-commerce
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Published: 16 March 2008
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View all- Endres MKastner JRudenko L(2018)Analyzing and Clustering Pareto-Optimal Objects in Data StreamsLearning from Data Streams in Evolving Environments10.1007/978-3-319-89803-2_4(63-91)Online publication date: 29-Jul-2018
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