초록
영어
In this paper, in order to reduce scarcity and improve accuracy, a factor that seriously affects the accuracy of the collaborative filtering system, which is one of the methods for providing intelligent personalized app services, we create a user function matrix after purifying all log data of webmail users. Using the collaborative filtering g)-based Euclidean distance measurement method, a process of comparing user data and group data, comparing user data and group data after calculating the similarity of function usage patterns between users, We proposed a method to provide customized services for each user by extracting each user's service usage pattern.
목차
Abstract
Ⅰ. Introduction
Ⅱ. Results and Discussion
2.1. Data Optizization
2.2. Matrix creation
2.3. Composition of Nearest Neighbors
2.4. Measurement of similarity between groups
Ⅲ. Conclusion
References
Ⅰ. Introduction
Ⅱ. Results and Discussion
2.1. Data Optizization
2.2. Matrix creation
2.3. Composition of Nearest Neighbors
2.4. Measurement of similarity between groups
Ⅲ. Conclusion
References
저자정보
참고문헌
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