Find in Library
Search millions of books, articles, and more
Indexed Open Access Databases
Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making
oleh: Ritesh Kumar, Partha Sarathi Bishnu
Format: | Article |
---|---|
Diterbitkan: | SpringerOpen 2019-10-01 |
Deskripsi
Abstract Customers demand typical type of products with multiple features. We want to develop a business intelligence system which helps the company to set the blue ocean strategy by discovering k-most promising features (k-MPF) from the customers’ query and a set of existing products of the similar type. In this paper, we have formulated k-MPF to set the blue ocean strategy with compatible features. We have experimented with our proposed algorithms using different synthetic and real datasets, and the results showed the effectiveness of our proposed algorithms.