Title: Environmental art social networks modelling and information mining framework based on green computing

Authors: Yan Tian

Addresses: Art Department, Xinxiang Vocational and Technical College, Henan Xinxiang, 453000, China; College of Education, St. Paul University Manila, Malate, Manila, 1004, Philippines

Abstract: The number of internet information is growing exponentially, with hundreds of millions of web pages that require a large demand on the computational efficiency. Users in social media can establish various relationships, which results in a variety of virtual online social networks. Social network service data is essentially a network data structure, and e-commerce website data can also be abstracted as a two-part graph composed of users and goods. In recent years, with collaborative filtering, local diffusion and other algorithms widely used in the recommendation system of e-commerce websites, network information mining has brought huge benefits for e-commerce websites, and the user experience has been improved rapidly. This paper studies the environmental art social network modelling and information mining model based on green computing. The novel computational model is designed for the systematic construction and algorithm is applied to real applications. The experimental results show effectiveness of the proposed method.

Keywords: green computing; cloud computing model; environmental art; social network; modelling; information mining.

DOI: 10.1504/IJART.2021.10043660

International Journal of Arts and Technology, 2021 Vol.13 No.4, pp.279 - 299

Received: 24 Mar 2021
Accepted: 10 Oct 2021

Published online: 23 Feb 2022 *

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