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OALib Journal期刊
ISSN: 2333-9721
费用:99美元
投稿
时间不限
( 2024 )
( 2023 )
( 2022 )
( 2021 )
自定义范围…
The traditional library can’t provide the service of personalized recommendation for users. This paper used Clementine to solve this problem. Firstly, model of K-means clustering analyze the initial data to delete the redundant data. It can avoid scanning the database repeatedly and producing a large number of false rules. Secondly, the paper used clustering results to perform association rule mining. It can obtain valuable information and achieve the service of intelligent recommendation.