Bio
Dr. N Pughazendi is an Associate Professor in Computer Science at Panimalar Engineering College, Chennai, affiliated with Anna University, India. He holds an M.E. and Ph.D. and has made significant contributions to the field of computer science, particularly in temporal databases and data mining. His notable work includes the paper 'Discovering Patterns from Temporal Databases using Temporal Association Rule.' With a strong academic background and extensive experience as a reviewer for the Global Journal of Computer Science and Technology (GJCST), Dr. Pughazendi has supervised multiple research scholars and led several research projects. His expertise spans general and broad streams of computer science, and he continues to advance knowledge in his domain through teaching, research, and scholarly review activities.
Educational Journey
M.E, Ph.D.,
Experience
Editors Role
Reviewer
GJCST
2016 -Research
DISCOVERING PATTERNS FROM TEMPORAL DATABASES USING TEMPORAL ASSOCIATION RULE
Data mining is the process of discovering and examining data from diverse viewpoint, using automatic or semiautomatic techniques to remove knowledge or useful information and discover correlations or meaningful patterns and rules from large databases. One of the most vital characteristic missed by the traditional data mining systems is their capability to record and process time-varying aspects of the real world databases. . Temporal data mining, which mines or discovers knowledge and patterns from temporal databases, is an extension of data mining with capability to include time attribute analysis. The pattern discovery task of temporal data mining discovers all patterns of interest from a large dataset. This paper presents an overview of temporal data mining and focus on pattern discovery using temporal association rules.
