A Study on Post Mining of Association Rules Targeting User Interest
Association Rule Mining means discovering interesting patterns with in large databases. Association rules are used in many application areas such as market base analysis, web log analysis, protein substructures. Several post processing methods were developed to reduce the number of rules using non-redundant rules or pruning techniques such as pruning, summarizing, grouping or visualization based on statistical information in the database. As such, problem of identifying interest rules remind the same. Methods such as Rule deductive method, Stream Mill Miner (SMM), a DSMS (Data Stream Management Systems), Medoid clustering technique (PAM: Partitioning Around Medoids), Constraint-based Multi-level Association Rules with an ontology support were developed but are not effective.