Efficient and domain-invariant competitor mining
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient influence-based processing of market research queries
Proceedings of the 21st ACM international conference on Information and knowledge management
Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
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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.