Large databases of temporal records have made it possible for researchers
to verify their hypotheses related to temporal event sequences.
However, with the overwhelming size of data and numerous
possible patterns, an important issue is what patterns should
be highlighted and presented to users. We implement a visualization
tool, PairFinder, to enable users to efficiently locate patterns of
interest. Users can 1) see all the results of the potential event patterns
and 2) use interestingness measures to rank event patterns by
their interestingness. In addition, users can hide irrelevant patterns
and filter records by record attributes. By looking only at the topranked
patterns, users can easily scan large number of patterns. We
demonstrate the potential of PairFinder with four case studies and
summarize the patterns found in the data sets.
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