  The problem of frequent pattern mining from non-temporal databases is studied
extensively by various researchers working in areas of data mining, temporal
databases and information retrieval. However, Conventional frequent pattern
algorithms are not suitable to find similar temporal association patterns from
temporal databases. A Temporal database is a database which can store past,
present and future information. The objective of this research is to come up
with a novel approach so as to find similar temporal association patterns w.r.t
user specified threshold and a given reference support time sequence using
concept of Venn diagrams. For this, we maintain two types of supports called
positive support and negative support values to find similar temporal
association patterns of user interest. The main advantage of our method is
that, it performs only a single scan of temporal database to find temporal
association patterns similar to specified reference support sequence. This
single database scan approach hence eliminates the huge overhead incurred when
the database is scanned multiple times. The present approach also eliminates
the need to compute and maintain true support values of all the subsets of
temporal patterns of previous stages when computing temporal patterns of next
stage.
