Big Data Analysis Applied To Retailers Recommended System

• Main Authors: Chien-huan Luh, 陸建寰
• Other Authors: Wen-hwa Liao
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/urgka7

碩士 === 大同大學 === 資訊經營學系(所) === 106 === With the rapid development of information and network technology, huge amounts of data have become a new trend in the field of global information and services. Due to the complexity and diversity of information, how to find out real useful information from the huge amount of data employing big data analysis will be the key issue for companies to win the business competition. Although E-commerce is convenient and express, there are still many customers who like to personally touch, try on and purchase goods in the retail stores. This study employs the recommendation system on the retail store and enables the situation closer to the real one. Additionally, a modified collaborative filtering method with weight distribution is proposed to increase its accuracy. The consumers could find the products they need more quickly with the aid of the personalized recommendation system. Moreover, it can be utilized to analyze the consumers’ past consumption information and thus predict the consumer’s preference for the products they purchased. Therefore, the companies can provide consumers with more appropriate services and reduce the wasted shopping time. In addition to improving the customer loyalty and realizing industrial intelligence, big data analysis can increase more profit to the industry.