Open AccessAutomatic Recommendation Method of Network Data Based on Big Data Technology
Author(s) -
Xiaorui Huang,
Shaohui Guo,
Yunchu Zhang,
Peidong Zhang,
Shiyuan Xu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1550/3/032120
Subject(s) - computer science , property (philosophy) , big data , recommender system , the internet , data mining , collaborative filtering , order (exchange) , data science , information retrieval , world wide web , philosophy , epistemology , finance , economics
With the advent of the Internet era in modern society, the surge in network data has greatly increased the difficulty for users to obtain demand information. In order to provide customers with information that may be of interest to them, this paper proposes a belief collaborative recommendation optimization algorithm, which introduces DP synthesis rules and Smets synthesis rules to improve traditional DS synthesis rules and establishes network data recommendation models. This method realizes automatic recommendation of network data according to the self-property and historical behavior data of network customers. The experimental results show that the automatic recommendation method for network data proposed in this paper has higher recommendation accuracy.