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协同过滤推荐中一种改进的信息核提取方法.
- Source :
-
Application Research of Computers / Jisuanji Yingyong Yanjiu . Jan2020, Vol. 37 Issue 1, p140-143. 4p. - Publication Year :
- 2020
-
Abstract
- Aiming at the scalability problem in collaborative filtering recommendation algorithm, on the basis of the original information core extraction method based on FB and RB, this paper proposed an improved extraction information core method IFB and IRB. When in search of the most similar neighbors, it proposed a concept: optimization set, and found the most similar neighbors for each user on this set. The experimental results show that this method can get more accurate recommendation results, and reduce the mean average absolute error( MAE) effectively. At the same time, it has higher precision and recall, so it has better recommendation effect. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DATA mining
*RECOMMENDER systems
*SCALABILITY
*NEIGHBORS
*ALGORITHMS
*CONCEPTS
Subjects
Details
- Language :
- Chinese
- ISSN :
- 10013695
- Volume :
- 37
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Application Research of Computers / Jisuanji Yingyong Yanjiu
- Publication Type :
- Academic Journal
- Accession number :
- 141036767
- Full Text :
- https://doi.org/10.19734/j.issn.1001-3695.2018.05.0450