Abstract
Similarity profiled association mining from time stamped transaction databases is an important topic of research relatively less addressed in the field of temporal data mining. Mining temporal patterns from these databases requires choosing and applying similarity measure for pruning patterns after computing similarity degree. This paper proposes a new z-space based similarity measure KRISHNA SUDARSANA for time-stamped transaction databases. Applying KRISHNA SUDARSANA requires moving the threshold value given by user to a different transformation space (z-space) and is a function of standard deviation. A new expression for standard deviation is derived for use in the expression for similarity measure. This research extends the similarity measure SRIHASS by using a product based membership function.
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