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Collaborative filtering algorithms, such as matrix factorization techniques, are recently gaining momentum due to their promising performance on recommender systems. However, most collaborative filtering algorithms suffer from data sparsity. Active learning algorithms are effective in reducing the sparsity problem for recommender systems by requesting users to give ratings to some items when they...
An accurate prediction of crude oil output is crucial to oilfield enterprise in reasonable production arrangement and the production management improvement. This paper proposes a RS-C4.5 data mining method based on the rough set theory and decision tree C4.5 algorithm to predict the crude oil output. Firstly, relevant data of crude oil production is pre-processed by K-Means algorithm to obtain a discrete...
Factors that affect crude oil output are multifarious and non-linear, so it is very difficult to analyze and predict the crude oil output solely based on mathematical methods. This paper presents a new method that applies TB-SCM algorithm to predict crude oil output. Firstly, the monthly production data of the past years from a sample oil plant is preprocessed by the K-means algorithm, and the transaction...
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