The importance of skyline analysis has been well recognized in business intelligence applications, such as decision making for marketing . Most previous works study how to help customers find a set of best products from a pool of given products. In this work, we identify a new problem, creating competitive products. Given a set of products in the existing market, we want to study how to create a set of best possible products such that the newly created products are not dominated by the products in the existing market. There exists a straightforward solution to materialize all possible products and check for dominance relationships. However, this approach is not unscalable for large data sets. In this work, we propose an approach to effectively support this query. An extensive performanc...[ Read more ]

The importance of skyline analysis has been well recognized in business intelligence applications, such as decision making for marketing . Most previous works study how to help customers find a set of best products from a pool of given products. In this work, we identify a new problem, creating competitive products. Given a set of products in the existing market, we want to study how to create a set of best possible products such that the newly created products are not dominated by the products in the existing market. There exists a straightforward solution to materialize all possible products and check for dominance relationships. However, this approach is not unscalable for large data sets. In this work, we propose an approach to effectively support this query. An extensive performance study using both synthetic and real data sets is reported to verify its effectiveness and efficiency.