Abstract

Transaction database is a collection of transactions along with the related time stamps. These transactions are defined using some prototypes. They are called as the Transitional patterns that denote the vibrant nature of the frequent patterns in the database. The considerable high points for the transaction database are the timestamps also called as time durations. They are the points that have the alteration in the recurrence of the prototypes. There is majorly couple of stages in existing TP-Mine algorithm. The initial stage is to find out the frequent patterns and the second stage is to discover Transitional patterns or the styles and the significant milestones. These patterns consist of the two kinds of the styles likely the positive one and the negative one. In the previous time cases the effort that was made on the research was to build up the algorithms by planning the total series of the transitional patterns. In our paper we consider that the alterations made in the consequent period regarding the total concept of database is not noteworthy. So for this reason we have put forward an entirely latest transitional patterns methodology called periodical transitional pattern mining. The experimental outputs are appealing and apparent those were produced by this periodical transitional pattern mining and has high importance that when evaluated utilizing the present patterns.

How to Cite
, D.SUJATHA, P.Shyamala. PTP-Mine: Range Based Mining of Transitional Patterns in Transaction Databases. Global Journal of Computer Science and Technology, [S.l.], feb. 2012. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/438>. Date accessed: 25 jan. 2021.