Conceptual Design of Incremental Matrix Consolidation Operation for Recommendation Systems  
Author Nam D. Vo


Co-Author(s) Hoang Long Nguyen; Gen Li; Jason J. Jung; David Camacho


Abstract In this paper, we propose a method for consolidating multiple matrices incrementally for recommendation system. Based on mathematical approach methods, we unify multiple matrices together based on the overlap of the utility matrix. Specifically, we suggest a procedure to consolidate matrices together. Then the recommendation system can use the unification matrix to produce the item predictions for users.


Keywords Data consolidation; Data unification; Recommendation system; Matrix factorization.
    Article #:  DSBFI19-87
Proceedings of ISSAT International Conference on Data Science in Business, Finance and Industry
July 3-5, 2019 - Da Nang, Vietnam