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Mining Frequent Patterns Using Self-Organizing Map
Research and Trends in Data Mining Technologies and Applications
Association rule mining is one of the most popular pattern discovery methods used in data mining. Frequent pattern extraction is an essential step in association rule mining. Most of the proposed algorithms for extracting frequent patterns are based on the downward closure lemma concept utilizing the support and confidence framework. In this paper we investigate an alternative method for mining frequent patterns in a transactional database. Self-Organizing Map (SOM) is an unsupervised neuraldoi:10.4018/978-1-59904-271-8.ch005 fatcat:vrbzzgmmwjcixes5vhs5vl6j4y