Faceted metadata for image search and browsing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
IEEE Transactions on Knowledge and Data Engineering
Multi-objective query processing for database systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Webpage understanding: beyond page-level search
ACM SIGMOD Record
Towards a theory model for product search
Proceedings of the 20th international conference on World wide web
IEEE Transactions on Knowledge and Data Engineering
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Most product search engines today build on models of relevance devised for information retrieval. However, the decision mechanism that underlies the process of buying a product is different than the process of locating relevant documents or objects. We propose a theory model for product search based on expected utility theory from economics. Specifically, we propose a ranking technique in which we rank highest the products that generate the highest surplus, after the purchase. We instantiate our research by building a demo search engine for hotels that takes into account consumer heterogeneous preferences, and also accounts for the varying hotel price. Moreover, we achieve this without explicitly asking the preferences or purchasing histories of individual consumers but by using aggregate demand data. This new ranking system is able to recommend consumers products with "best value for money" in a privacy-preserving manner. The demo is accessible at http://nyuhotels.appspot.com/