DocumentCode :
3144391
Title :
Finding top-k profitable products
Author :
Wan, Qian ; Wong, Raymond Chi-Wing ; Peng, Yu
Author_Institution :
Comput. Sci. & Eng. Dept., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear :
2011
fDate :
11-16 April 2011
Firstpage :
1055
Lastpage :
1066
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.
Keywords :
decision making; industrial economics; profitability; set theory; dominance analysis; market; multicriteria decision making; real datasets; skyline analysis; subset; top-k profitable products; Companies; Complexity theory; Dynamic programming; Greedy algorithms; Heuristic algorithms; Indexes; Portable computers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2011 IEEE 27th International Conference on
Conference_Location :
Hannover
ISSN :
1063-6382
Print_ISBN :
978-1-4244-8959-6
Electronic_ISBN :
1063-6382
Type :
conf
DOI :
10.1109/ICDE.2011.5767895
Filename :
5767895
Link To Document :
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