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

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.