Document Type : Primary Research paper
Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India VIT Bhopal University, Madhya Pradesh, India
The Global Apparel Sector projects a higher growth value of the overall economy. Fashion apparel business is always an ongoing process as long as mankind is existent on earth since clothing is one of our essentials. But the only thing that keeps this industry on spree is the changing consumer behavior patterns. This change in buying pattern is immensely influenced by the demographics and psychographics. Brands are forced to formulate strategies that best serve the needs and expectations of consumers. Satisfaction with emotional bonding is the key to success of brands these days. Also the buying behavior of the customer is widely affected by many factors. With all these measures, it really makes the process tough to bring in a strategy for fashion business based on the customer’s buying patterns. Mining and preserving high utility itemsets from fashion data with all the dimensions, allows a business to plan a strategy to improve the profit and also it is important to preserve such valuable information from being discovered. The paper discusses the algorithms that work perfectly on fashion data being affected by multiple factors with the combination of privacy preservation.