A Crowdsourcing Recommender System based on Fuzzy Logic and Collaborative Filtering

• Main Authors: Gia Tuan Vuong, 王嘉俊
• Other Authors: Ming-Che Hsieh
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/ka4psn

碩士 === 國立臺東大學 === 資訊管理學系碩士班 === 106 === With the development of Internet, big data and Internet of Things, the industry is rapidly upgrading. How to use network technology to connect experts in various fields to help industrial upgrading is becoming more and more important, especially in Taitung where information is scarce and traffic is not convenient. This study proposed a recommender mechanism based on fuzzy logic and collaborative filtering, and realized the crowdsourcing recommender system for local industries in Taitung. Fuzzy logic was used to infer the satisfaction of experts and the maturity of the LOHAS industry. The collaborative filtering was applied to the calculation of the similarity of experts and the similarity of industries. By implementing this study and establishing a system, local industries can find the right experts and scholars to tackle their problems more easily and effectively. Experienced experts can also find a suitable industry, give full play to their talents, speed up cooperation between industry and academia, and promote the development of the LOHAS industry and circular economy.