Association Rule in Data Mining For Large Transactional Database Maheshwari Abhishek Kumar Lecturer (MCA), Venkateshwara School of Computer Science, Meerut Online published on 26 June, 2013. Abstract Data mining is a technology to explore, analyze (knowledge discovery from data) the data and At last, extract the interesting (non-trivial, implicit, previously unknown and potentially useful) pattern or knowledge from huge amount of data. In this paper, we discuss about the problem in online mining of data in large transactional database, here we apply association rule for mining the data which helps to remove the redundant rule and helps in compact representation of rules for user. In this paper, optimized algorithm has been proposed for online rule generation. The advantage of this algorithm is that the graph generated in our algorithm has less edge as compared to the lattice used in the existing algorithm. This algorithm generated all the essential rules and no rule is missing. The use of non redundant association rules help significantly in the reduction of irrelevant noise in the data mining process. Top Keywords Database Management, Database Applications-Data Mining, Transactional Database, Adjacency lattice, Graph theoretic Approach, Online Rule Generation, Algorithms, Performance, Experimentation, Verification. Top |