Incremental Temporal Mining using Incremental TPMiner and Incremental P-TPMiner Algorithms

Temporal data mining is one type of "predictive”. Temporal Association mining is sequential mining. We usually predict what will happen next or what is probability that certain thing happen Sequential pattern mining is one important case of data mining. Most of sequential pattern mining algorithm works on static data which deals with the database should not change. But the databases in real world application do not have static data rather they have incremental database. There are some applications using temporal event data have used to discovering patterns from events. There are two types of interval-based patterns: Temporal pattern and Probabilistic temporal pattern are proposed. This paper attempts to provide two algorithms Incremental Temporal Pattern Miner (TP-Miner) and Probabilistic Temporal Pattern Miner (P-TP Miner).In this project, apply proposed algorithms to real datasets to make the comparison of Incremental temporal mining and Non-incremental temporal mining.