A Survey on Transitional Pattern Mining in Online Transactional Databases

The process of extracting interesting implicit knowledge from large information repositories like relational databases, data warehouse etc. and summarizing into useful information is called as Data Mining. Data Mining is also known as knowledge discovery in databases, knowledge extraction, business intelligence etc. Data mining should be applicable to any kind of data repository as well as to transient data such as data streams. A transactional database consists of a file where each record represents a transaction. Frequent patterns are patterns that occur frequently in data. There are various approaches proposed for frequent pattern mining. But this paper is discussing about transitional patterns that are patterns whose frequency dramatically changes over time and various approaches of frequent pattern mining that do not consider the time stamp of each transaction.