Algorithm of key data ensemble clustering and approximate analysis in cloud computing
by Xia Wendong; Liu Yuanfeng; Chen Deli
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 9, No. 3/4, 2017

Abstract: One collaborative data fusion recommendation algorithm is SFS-TOPSIS based on customer satisfaction degree. First, it starts from calculation efficiency and recommended precision angle that improves service recommendation algorithm, makes real-time updating and algorithm improvement for it by combining time-varying weight method TOPSIS fusion algorithm and designs a collaborative data fusion recommendation algorithm based on customer satisfaction degree. Second, for the problem of inadequate definition of traditional similarity for resolution, improvements have been made based on user evaluation confidence. Last, time-varying weight method has been adopted to improve standard TOPSIS fusion, improve time-varying attribute of TOPSIS decision fusion and realise effective attribute fusion of user similarity data; through making simulation comparison on two standard testing sets of MovieLens and BookCrossing, it indicates that the service recommendation performance of SFS-TOPSIS is superior. The proposed SFS-TOPSIS algorithm can improve service recommendation accuracy effectively and it is with certain application value.

Online publication date: Tue, 27-Feb-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reasoning-based Intelligent Systems (IJRIS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com