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Article | 14-October-2020

Research on Commodity Mixed Recommendation Algorithm

performs global summarization, which greatly improves the efficiency of the algorithm. This article mainly studies the distributed recommendation algorithm under the Hadoop platform. The recommendation algorithm combines the decision tree and the collaborative filtering algorithm, and improves the traditional collaborative filtering algorithm to improve the timeliness of recommendation. II. INTRODUCTION TO RELATED TECHNOLOGIES A. Introduction to the traditional collaborative filtering algorithm

Hao Chang, Shengquan Yang

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 3, 1–8

Article | 07-May-2018

A Collaborative Filtering Recommendation Algorithm with Improved Similarity Calculation

In order to improve the accuracy of the proposed algorithm in collaborative filtering recommendation system, an Improved Pearson collaborative filtering (IP-CF) algorithm is proposed in this paper. The algorithm uses the user portrait, item characteristics and data of user behavior to compute the baseline predictors model. Instead of the traditional algorithm’s similarity calculation, the prediction model is used to improve the accuracy of the recommendation algorithm. Experimental results on

Yang Ju, Liu Bailin, Zhixiang Zhao

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 1, 97–100

Article | 07-May-2018

Design and Implementation of Music Recommendation System Based on Hadoop

, database and ETL operation, which can calculate a set of complete recommendation system from user operation end to server and data calculation. In order to improve the accuracy of the recommendation algorithm, this paper introduces k-means clustering algorithm to improve the recommendation algorithm based on user-based collaborative filtering.The experimental results show that the accuracy of the proposed algorithm has been significantly improved after the introduction of k-means.

Zhao Yufeng, Li Xinwei

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 2, 126–132

Article | 01-March-2015


This article introduces ensemble learning algorithms in recommender systems, and in boosting algorithm framework of this article, shows how to filter the basic recommendation algorithm according to the characteristics of boosting algorithm. By comparing the rational choice of the two recommended boosting algorithm is applied to the frame. And then it determines the main parameters of the algorithm through the experiments, ultimately to obtain a more effective integration of the recommendation

Cheng Lili

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 368–386

research-article | 30-November-2020

Research on Mobile Point Exchange System Based on Collaborative Filtering Recommendation Algorithm

I. INTRODUCTION The personalized recommendation system has played a vital role in the development of ecommerce platforms. In order to better serve customers, the system adopts a collaborative filtering recommendation algorithm, which is a commonly used recommendation algorithm in many e-commerce systems. When the user is performing an operation, the system will record the user’s operation log, including the behavior track of which products the user has viewed, favorite products, and sharing or

Leijie Feng, Zehui Mu

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 2, 65–72

Article | 30-November-2018

Traveling Route Generation Algorithm Based On LDA and Collaborative Filtering

filtering algorithms. This paper reviews the related research of collaborative filtering. Firstly, it expounds the connotation of collaborative filtering and its main situation, including sparsity, multi-content and scalability, and then detail the solutions for domestic and foreign scholars. This article is very helpful for the study and research of collaborative filtering algorithms. Qiang C, et al. has proposed a recommendation algorithm based on label and collaborative filtering. The label is used

Peng Cui, Yuming Wang, Chunmei Li

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 4, 47–62

research-article | 30-November-2020

Design of Intelligent Warehouse Management System Based on MVC

order to improve the efficiency of warehousing and reduce transportation costs, proposed a coordinated optimization algorithm for cargo location and AGV path [3]. The system adds a product recommendation function to the warehouse management, and proposes a collaborative filtering recommendation algorithm for products based on user preferences. This paper designs and develops an intelligent warehouse management system based on MVC. Its application can make warehouse management more convenient, save

Ping Lu, Pingping Liu, Jiangtao Xu

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 2, 79–87

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