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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 | 30-November-2018

Traveling Route Generation Algorithm Based On LDA and Collaborative Filtering

reduce the blindness and randomness of route arrangement, then provide customers with personalized travel routes, thus providing more travel options for users to choose has gradually become a research hotspot of relevant enterprises and disciplines. In recent years, algorithms for travel route generation, LDA, and collaborative filtering have been reported many times. Ma Zhangbao et al. [2], who began with the space decision-making of tourism travel, studied methods and techniques of the tourism

Peng Cui, Yuming Wang, Chunmei Li

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

Article | 14-October-2020

Research on Commodity Mixed Recommendation Algorithm

necessary to adopt a big data model for analysis. Compared with the traditional data model using random analysis (sampling survey), the big data model analyzes all data and has the characteristics of 4V, Namely Large Volume, High Speed, Variety, Value. Collaborative filtering algorithm is one of the most concise and practical recommendation algorithms. If you use traditional data model for sampling survey, it will inevitably aggravate the sparsity problem of the algorithm itself, so it is of great

Hao Chang, Shengquan Yang

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

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

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

Article | 01-March-2015

RECOMMENDER ALGORITHMS BASED ON BOOSTING ENSEMBLE LEARNING

Cheng Lili

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

Research Article | 01-September-2017

LEARNING TO RANK AND CLASSIFICATION OF BUG REPORTS USING SVM AND FEATURE EVALUATION

S. Rajeswari, S. Sharavanan, R. Vijai, RM. Balajee

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 311–329

Article | 07-May-2018

Design and Implementation of Music Recommendation System Based on Hadoop

Zhao Yufeng, Li Xinwei

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

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