Construction on Virtualized Environment for Digital Library Based on Cloud Computing Technology

2014 ◽  
Vol 687-691 ◽  
pp. 3019-3022 ◽  
Author(s):  
Jun Jun Liu
Keyword(s):  
Cloud Computing ◽  
Digital Library ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Computing Environment ◽  
Computing Technology ◽  
Cloud Computing Environment ◽  
Key Technology ◽  
Virtualization Technology

Cloud computing technology is emerging technology in the field of information technology, and its technical advantage has brought new opportunities and challenges for the development and service of digital library in the Internet era. Virtualization is the key technology of cloud computing, and the paper discusses the virtualization of digital library in the cloud computing environment from technical level. Firstly, the paper introduced cloud computing and virtualization technology; then created a virtualized environment for digital library based on the cloud computing technology, and described the function of various levels; finally, the capacity of virtual machines appointment scheduling can be calculated according to formulas. The paper has great significance in enhancing the efficiency and quality of library service, constructing resource sharing system of digital library.

Personalized Recommendation Mechanism Based on Collaborative Filtering in Cloud Computing Environment

2021 ◽  
pp. 751-769
Author(s):  
Xinling Tang ◽  
Hongyan Xu ◽  
Yonghong Tan ◽  
Yanjun Gong
Keyword(s):  
Cloud Computing ◽  
Collaborative Filtering ◽  
Large Scale ◽  
Nearest Neighbor ◽  
Distributed Storage ◽  
Distributed Processing ◽  
Storage System ◽  
Personalized Recommendation ◽  
Computing Environment ◽  
Cloud Computing Environment

With the advent of cloud computing era and the dramatic increase in the amount of data applications, personalized recommendation technology is increasingly important. However, due to large scale and distributed processing architecture and other characteristics of cloud computing, the traditional recommendation techniques which are applied directly to the cloud computing environment will be faced with low recommendation precision, recommended delay, network overhead and other issues, leading to a sharp decline in performance recommendation. To solve these problems, the authors propose a personalized recommendation collaborative filtering mechanism RAC in the cloud computing environment. The first mechanism is to develop distributed score management strategy, by defining the candidate neighbors (CN) concept screening recommended greater impact on the results of the project set. And the authors build two stage index score based on distributed storage system, in order to ensure the recommended mechanism to locate the candidate neighbor. They propose collaborative filtering recommendation algorithm based on the candidate neighbor on this basis (CN-DCF). The target users are searched in candidate neighbors by the nearest neighbor k project score. And the target user's top-N recommendation sets are predicted. The results show that in the cloud computing environment RAC has a good recommendation accuracy and efficiency recommended.

Personalized Recommendation Mechanism Based on Collaborative Filtering in Cloud Computing Environment

2017 ◽  
Vol 12 (3) ◽  
pp. 11-27 ◽  
Author(s):  
Xinling Tang ◽  
Hongyan Xu ◽  
Yonghong Tan ◽  
Yanjun Gong
Keyword(s):  
Cloud Computing ◽  
Collaborative Filtering ◽  
Large Scale ◽  
Nearest Neighbor ◽  
Distributed Storage ◽  
Distributed Processing ◽  
Storage System ◽  
Personalized Recommendation ◽  
Computing Environment ◽  
Cloud Computing Environment

With the advent of cloud computing era and the dramatic increase in the amount of data applications, personalized recommendation technology is increasingly important. However, due to large scale and distributed processing architecture and other characteristics of cloud computing, the traditional recommendation techniques which are applied directly to the cloud computing environment will be faced with low recommendation precision, recommended delay, network overhead and other issues, leading to a sharp decline in performance recommendation. To solve these problems, the authors propose a personalized recommendation collaborative filtering mechanism RAC in the cloud computing environment. The first mechanism is to develop distributed score management strategy, by defining the candidate neighbors (CN) concept screening recommended greater impact on the results of the project set. And the authors build two stage index score based on distributed storage system, in order to ensure the recommended mechanism to locate the candidate neighbor. They propose collaborative filtering recommendation algorithm based on the candidate neighbor on this basis (CN-DCF). The target users are searched in candidate neighbors by the nearest neighbor k project score. And the target user's top-N recommendation sets are predicted. The results show that in the cloud computing environment RAC has a good recommendation accuracy and efficiency recommended.

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