| Abstrakt: |
One of the most essential jobs in extracting meaningful and usable information from raw data is pattern mining. The goal of this job is to find item sets that represent any patterns of data. The performance of conventional pattern mining approaches has deteriorated. The purpose of this study is to aims to offer novel pattern mining algorithms that are both efficient and effective.in the field of big data In order to do this, most used maximal frequent pattern algorithm based on The Hadoop open-source implementation and the MapReduce framework have been presented. A diverse variety of large data datasets were evaluated to test the performance of the suggested method, we evaluate the our proposed method data contain 31019 transactions, their 5 million singletons. Comparisons against extremely FPmax pattern mining algorithm are part of the experimentation stage. [ABSTRACT FROM AUTHOR] |
