Proposing An Efficient Method For Frequent Pattern Mining
Vaibhav Kant Singh, Shah, Vijay, Yogendra Kumar Jain, Anupam Shukla, A. S. Thoke, Vinay KumarSingh, Chhaya Suryabhan Dule, Vivek Parganiha · Zenodo (CERN European Organization for Nuclear Research) · 2008
Data mining, which is the exploration of knowledge from the large set of data, generated as a result of the various data processing activities. Frequent Pattern Mining is a very important task in data mining. The previous approaches applied to generate frequent set generally adopt candidate generation and pruning techniques for the satisfaction of the desired objective. This paper shows how the different approaches achieve the objective of frequent mining along with the complexities required to perform the job. This paper will also look for hardware approach of cache coherence to improve efficiency of the above process. The process of data mining is helpful in generation of support systems that can help in Management, Bioinformatics, Biotechnology, Medical Science, Statistics, Mathematics, Banking, Networking and other Computer related applications. This paper proposes the use of both upward and downward closure property for the extraction of frequent item sets which reduces the total number of scans required for the generation of Candidate Sets.