Distributed Singular Value Decomposition Method for Fast Data Processing in Recommendation Systems

Abstract

The problem of analyzing a big amount of user data to determine their preferences and, based on these data, to provide recommendations on new products is important. Depending on the correctness and timeliness of the recommendations, significant profits or losses can be obtained. The task of analyzing data on users of services of companies is carried out in special recommendation systems. However, with a large number of users, the data for processing become very big, which causes complexity in the work of recommendation systems. For efficient data analysis in commercial systems, the Singular Value Decomposition (SVD) method can perform intelligent analysis of information. With a large amount of processed information we proposed to use distributed systems. This approach allows reducing time of data processing and recommendations to users. For the experimental study, we implemented the distributed SVD method using Message Passing Interface, Hadoop and Spark technologies and obtained the results of reducing the time of data processing when using distributed systems compared to non-distributed ones.

Collaborative Filtering Approach: Skincare Product Recommendation Using Singular Value Decomposition (Svd)

“…For data with a high rate of change, such as streaming for music, video, movies, and so all, SVD still performs well in making recommendations. When the data is abundant, SVD can overcome the sparsity matrix (Mohamed et al, 2020;Przystupa et al, 2021;Barathy & Citra, 2020).…”

On Novel System for Detection Video Impairments Using Unsupervised Machine Learning Anomaly Detection Technique

“…In the same time, the trace of matrix can discover the size of degradation in the observed matrix considering number of non-singular elements. According to [29] the trace of singular matrix represents energy distribution of source matrix or in this case time series. In the case of good correlation, the power will be concentrated in the first singular values while in the case of degradation the power of singular values in matrix will be distributed equally especially in the case of high disturbance.…”

Evaluation of Adhesive Joints Using Ultrasonic Rayleigh Waves

“…Testing the reliability of technical objects, including joints, is the subject of many articles [ 1 , 2 , 3 ] and constitutes the basis for improving manufactured machines and vehicles. One of the objects of reliability research is adhesive joints, widely used in every field of industry.…”