Research on Recommendation Algorithm Based on Information Entropy and Mahout
FAN Li
LIN Manshan
Abstract：Aiming at the noise data problem in recommendation algorithm offered by Mahout,the user entropy model is put for-ward.The user entropy model combines the concept of entropy in the information theory and uses the information entropy to measure the content of user information,which filters the noise data by calculating the entropy of users and getting rid of the users with low entropy.The proposed model is validated by using Mahout algorithm including user based collaborative filtering,collaborative filter-ing based on articles and Slope-One recommendation algorithm.The experimental results show that the proposed model can effec-tively filter out noise data,and the mean absolute error hava been decreased.
Keywords：noisedatainformation entropy modelMahoutrecommendation
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1903-1906,1918 )