DocumentCode :
2181661
Title :
Improving product search with economic theory
Author :
Beibei Li ; Ipeirotis, Panagiotis G. ; Ghose, Anindya
Author_Institution :
Dept. of Inf., Oper. & Manage. Sci., New York Univ., New York, NY, USA
fYear :
2010
fDate :
1-6 March 2010
Firstpage :
293
Lastpage :
296
Abstract :
With the growing pervasiveness of the Internet, online search for commercial goods and services is constantly increasing, as more and more people search and purchase goods from the Internet. Most of the current algorithms for product search are based on adaptations of theoretical models devised for ¿classic¿ information retrieval. However, the decision mechanism that underlies the process of buying a product is different than the process of judging a document as relevant or not. So, applying theories of relevance for the task of product search may not be the best approach. 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 consumer surplus after the purchase. In a sense, we rank highest the products that are the ¿best value for money¿ for a specific user. Our approach naturally builds on decades of research in the field of economics and presents a solid theoretical foundation in which further research can build on. We instantiate our research by building a search engine for hotels, and show how we can build algorithms that naturally take into account consumer demographics, heterogeneity of consumer preferences, and also account for the varying price of the hotel rooms. Our extensive user studies demonstrate an overwhelming preference for the rankings generated by our techniques, compared to a large number of existing strong baselines.
Keywords :
Internet; electronic commerce; information retrieval; purchasing; Internet; commercial goods; commercial services; economic theory; information retrieval; online search; product search improvement; Adaptation model; Business; Demography; Information management; Information retrieval; Multidimensional systems; Predictive models; Recommender systems; Search engines; Web and internet services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering Workshops (ICDEW), 2010 IEEE 26th International Conference on
Conference_Location :
Long Beach, CA
Print_ISBN :
978-1-4244-6522-4
Electronic_ISBN :
978-1-4244-6521-7
Type :
conf
DOI :
10.1109/ICDEW.2010.5452727
Filename :
5452727
Link To Document :
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