Abstract
Notice of Violation of IEEE Publication Principles<br><br>"Cognitive Overhead Reducing Based on Collaborative Filtering in Project Management,"<br>by Hua Chen, Qin-Ming He, Jian-Fei Qian<br>in the Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, August 2006<br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.<br><br>This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.<br><br>Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:<br><br>"Eigentaste: A Constant Time Collaborative Filtering Algorithm,"<br>by Ken Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins,<br>in Information Retrieval, Vol. 4, No. 2, 2001, pp. 133-151<br><br> <br/> As projects are scaled up to share a large amount of data or to handle a large number of users, a large amount of data can be potentially available to project members, and the shared data can frequently change due to modifications by project members or external sources. Reducing cognitive load on users by better organizing coordination activity, by filtering unnecessary information, and by delivering key information can greatly increase the effectiveness of project management. In this paper, we propose an approach of cognitive overhead reducing based on collaborative filtering (CF) algorithm called personality diagnosis (CFCOR). Given a list of artifacts user had accessed in a project and a new artifact, we compute the probability that he or she need the new artifact
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