Title :
USO- a new Slope One algorithm based on modified user similarity
Author :
Sun, Mingtao ; Zhang, Hui ; Song, Shiyu ; Wu, Kejia
Author_Institution :
State Key Software Dev. Environ. Lab., Beihang Univ., Beijing, China
Abstract :
Recommendation algorithm based on collaborative filtering strategy has achieved great success in the field of personalized recommendation, However, based on collaborative filtering recommendation algorithm complexity is too high, over-fitting problem, the recommended accuracy requirements lead to the algorithm difficult to achieve in practical applications. Slope One algorithm greatly simplifies the complex process of collaborative filtering algorithm, dramatically reducing the recommended system and maintenance difficulty, but at the same time recommended the accuracy will decline. Recommended in order to take into account the recommendation algorithm of low complexity and high accuracy, the authors propose the improved algorithm based on the correct user similarity Slope One - USO algorithm The inspection results show that the algorithm can effectively improve the accuracy of the recommendation of the slope-one algorithm.
Keywords :
collaborative filtering; computational complexity; recommender systems; Slope One algorithm; USO algorithm; algorithm complexity; collaborative filtering recommendation; collaborative filtering strategy; maintenance difficulty; modified user similarity; over-fitting problem; personalized recommendation; recommendation accuracy; recommendation algorithm; recommendation complexity; Accuracy; Educational institutions; Slope One algorithm; collaborative filtering; recommender system; similarity measure;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2012 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-1932-4
DOI :
10.1109/ICIII.2012.6339847