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Paper Information

Journal:   JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS)   SPRING 2014 , Volume 11 , Number 1 (40); Page(s) 57 To 64.
 
Paper: 

New Algorithm For Tensor Based Recommendation System

 
 
Author(s):  Nasiri M.*, Rezghi S.M., Minaei B
 
* COMPUTER ENGINEERING FAC., IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGHY, IRAN
 
Abstract: 
In recent years, use of recommendation systems has been more. Existing challenges in recommendation system datasets are interesting for researchers. Using matrix decompositions and then tensor decompositions in recommendation system algorithms have less error and results in that most of new algorithms use them. In this paper we present a new algorithm that uses tensor decomposition and have three dimensions user-item-time. Our algorithm has better result in comparison with matrix decomposition with 2 dimension user-item. In this method we use time as an independent dimension and 3rd dimension. Experiments show that using time in decompositions has less error.
 
Keyword(s): RECOMMENDATION SYSTEM, TENSOR DECOMPOSITION, SPARSE DATA, DYNAMIC RECOMMENDATION
 
 
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+ Click to Cite.
APA: Copy

NASIRI, M., & REZGHI, S., & MINAEI, B. (2014). NEW ALGORITHM FOR TENSOR BASED RECOMMENDATION SYSTEM. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), 11(1 (40)), 57-64. https://www.sid.ir/en/journal/ViewPaper.aspx?id=370186



Vancouver: Copy

NASIRI M., REZGHI S.M., MINAEI B. NEW ALGORITHM FOR TENSOR BASED RECOMMENDATION SYSTEM. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS). 2014 [cited 2022January26];11(1 (40)):57-64. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=370186



IEEE: Copy

NASIRI, M., REZGHI, S., MINAEI, B., 2014. NEW ALGORITHM FOR TENSOR BASED RECOMMENDATION SYSTEM. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), [online] 11(1 (40)), pp.57-64. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=370186.



 
 
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