SCOPE: An Efficient One Pass Approach to Find Strongly Correlated Item Pairs

Abstract

This paper presents an efficient one pass technique, SCOPE (strongly correlated item pairs extraction), which finds all the strongly correlated item pairs from transaction database, without generating any candidate sets. We experimented with real and synthetic datasets and compared the performance of SCOPE with its other counterparts i.e. TAPER and TCP and found satisfactory.