Finding top-k profitable products

Qian Wan*, Raymond Chi Wing Wong, Yu Peng

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

35 Citations (Scopus)

Abstract

The importance of dominance and skyline analysis has been well recognized in multi-criteria decision making applications. Most previous studies focus on how to help customers find a set of best possible products from a pool of given products. In this paper, we identify an interesting problem, finding top-k profitable products, which has not been studied before. Given a set of products in the existing market, we want to find a set of k best possible products such that these new products are not dominated by the products in the existing market. In this problem, we need to set the prices of these products such that the total profit is maximized. We refer such products as top-k profitable products. A straightforward solution is to enumerate all possible subsets of size k and find the subset which gives the greatest profit. However, there are an exponential number of possible subsets. In this paper, we propose solutions to find the top-k profitable products efficiently. An extensive performance study using both synthetic and real datasets is reported to verify its effectiveness and efficiency.

Original languageEnglish
Title of host publication2011 IEEE 27th International Conference on Data Engineering, ICDE 2011
Pages1055-1066
Number of pages12
DOIs
Publication statusPublished - 2011
Event2011 IEEE 27th International Conference on Data Engineering, ICDE 2011 - Hannover, Germany
Duration: 11 Apr 201116 Apr 2011

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Conference

Conference2011 IEEE 27th International Conference on Data Engineering, ICDE 2011
Country/TerritoryGermany
CityHannover
Period11/04/1116/04/11

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