Association Rule Mining is a machine learning method for discovering the interesting relations between attributes in huge transaction database. Typically, algorithms generate number of association rules, from which it hard to extract structured knowledge and present this automatically form that would be suitable user. Recently, an information cartography has been proposed creating summaries vis...

The Thesis aims at in depth study of Graph based approach to find Association Rule Mining and Association Rule Mining without pre-assign weights and its implementation. In the past, several authors have proposed various association rule mining algorithms with and without pre-assigned weights. The Thesis consists of two parts. Part two consists of graph based association rule mining for primitiv...

Association rules shows us interesting associations among data items. It means that an association rule clearly defines that how a data item is related or associated with another data item. That is why these types of rules are called Association rules. And the procedure by which these rules are extracted and managed is known as Association rule mining. Classical association rule mining had many...

This project [4] centers on regional association rule mining and scoping in spatial datasets. We introduces a methodology for mining spatial association rules and proposes new algorithms to determine the scope of a spatial association rule. We develop a reward-based region discovery framework that employs clustering to find interesting regions. The framework is applied to solve two distinct reg...

Association rule mining is the process of finding some relations among the attributes/attribute values of huge database based on support value. Most existing association mining techniques are developed to generate frequent rules based on frequent itemsets generated on market basket datasets. A common property of these techniques is that they extract frequent itemsets and prune the infrequent it...

Association Rule Mining (ARM) is concerned with how items in a transactional database are grouped together. It is commonly known as market basket analysis, because it can be likened to the analysis of items that are frequently put together in a basket by shoppers in a market. From a statistical point of view, it is a semiautomatic technique to discover correlations among a set of variables. ARM...