DocumentCode :
528600
Title :
Collaborative Filtering Algorithm Introduced Factor of Authority and Trust
Author :
Jun, Tao ; Ning, Zhang
Author_Institution :
Sch. of Manage., Univ. of Shanghai for Sci. & Technol., Shanghai, China
fYear :
2010
fDate :
7-9 May 2010
Firstpage :
3819
Lastpage :
3821
Abstract :
The traditional collaborative filtering algorithm is too much emphasizing on the role of similarity of the predicted value that there have a higher Sparse Data and poor result of Recommendation. In addition to similarity, the user´s trust and authority are also an important factor that will affect the result of recommendation in the algorithm by analyzing. Proposing a new filtering method by introducing factor of authority and trust, by which the users have a more reasonable and reasonable assessment of the resources. Experiments show the effectiveness of the algorithm.
Keywords :
authorisation; information filtering; recommender systems; authority factor; collaborative filtering algorithm; recommendation result; trust factor; Artificial neural networks; Classification algorithms; Clustering algorithms; Collaboration; Filtering; Filtering algorithms; Software algorithms; authority; collaborative filtering; similarit; trust;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
Type :
conf
DOI :
10.1109/ICEE.2010.957
Filename :
5591800
Link To Document :
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