Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An approach to discovering temporal association rules
SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Language Support for Temporal Data Mining
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
A Framework for Temporal Data Mining
DEXA '98 Proceedings of the 9th International Conference on Database and Expert Systems Applications
Discovering Calendar-Based Temporal Association Rules
TIME '01 Proceedings of the Eighth International Symposium on Temporal Representation and Reasoning (TIME'01)
Finding calendar-based periodic patterns
Pattern Recognition Letters
Mining Calendar-Based Periodicities of Patterns in Temporal Data
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Mining Local Association Rules from Temporal Data Set
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
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The problem of finding association rules from a dataset is to find all possible associations that hold among the items, given a minimum support and confidence. This involves finding frequent sets first and then the association rules that hold within the items in the frequent sets. In temporal datasets as the time in which a transaction takes place is important we may find sets of items that are frequent in certain time intervals but not frequent throughout the dataset. These frequent sets may give rise to interesting rules but these can not be discovered if we calculate the supports of the item sets in the usual way. We call here these frequent sets locally frequent. Normally these locally frequent sets are periodic in nature. We propose modification to the Apriori algorithm to compute locally frequent sets and periodic frequent sets and periodic association rules.