Vague Set Theory for Profit Pattern and Decision Making in Uncertain Data

Problem of decision making, especially in financial issues is a crucial task in every business. Profit Pattern mining hit the target but this job is found very difficult when it is depends on the imprecise and vague environment, which is frequent in recent years. The concept of vague association rule is novel way to address this difficulty. Merely few researches have been carried out in association rule mining using vague set theory. The general approaches to association rule mining focus on inducting rule by using correlation among data and finding frequent occurring patterns. In the past years data mining technology follows traditional approach that offers only statistical analysis and discovers rules. The main technique uses support and confidence measures for generating rules. But since the data have become more complex today, it’s a requisite to find solution that deals with such problems. There are certain constructive approaches that have already reform the ARM. In this paper, we apply concept of vague set theory and related properties for profit patterns and its application to the commercial management to deal with Business decision making problem.

@article{Badhe2015,
  title     = {Vague Set Theory for Profit Pattern and Decision Making in Uncertain Data},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {6},
  number    = {6},
  year      = {2015},
  publisher = {The Science and Information Organization},
  author    = {Vivek Badhe and Dr. R.S Thakur and Dr. G.S Thakur},
  doi       = {10.14569/IJACSA.2015.060625},
  url       = {https://doi.org/10.14569/IJACSA.2015.060625}
}