Notice of Violation of IEEE Publication Principles: An Efficient Mining Algorithm for Top-k Strongly Correlated Item Pairs

Abstract

Notice of Violation of IEEE Publication Principles<br><br>"An Efficient Mining Algorithm for Top K Strongly Correlated Item Pairs"<br>by Qiang Li and Yongshi Zhang<br>in the Proceedings of the 4th International Conference on Internet Computing for Science and Engineering, December 2009, pp. 152-155<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>"Efficient Mining of Top-K Strongly Correlated Item Pairs Using One Pass Techniques"<br>by S. Roy, D.K. Bhattacharyya<br>in the Proceeding of the 16th International Conference on Advanced Computing and Communications, December 2008, pp. 416-412<br><br> <br/> This paper presents an efficient method, which finds top-k strongly correlated item pairs from transaction database, without generating any candidate sets. To reduce execution time, the proposed method uses a correlogram matrix based approach to compute support count of all item sets in a single scan over the database. From the correlogram matrix the correlation values of all the item pairs are computed and top-k correlated pairs are extracted very easily. The simplified logic structure makes the implementation of the proposed method more attractive. Experiments were taken with real and synthetic datasets and the performance of the proposed method was compared with its other counterparts.