spatial association rule mining is an important technique of spatial data mining. Mining spatial association rule is one of the most important branches in the field of spatial data, spatial data mining can extract the spatial patterns and characteristics, general relations of spatial and non spatial data and other data features in common that hidden in spatial database. This paper describes and...

This Paper Focuses on Analyzing Medical Data using Association Rule mining for Heart Attack Prediction. Association rule mining is one of the fundamental research topics in data mining and knowledge discovery that finds interesting association or correlation relation ship among a large set of data items and predicts the associative and correlative behaviors for new data. The Association rule mi...

Existing algorithms for mining association rule at multiple concept level, restricted mining strong association among the concept at same level of a hierarchy. However mining level-crossing association rule at multiple concept level may lead to the discovery of mining strong association among at different level of hierarchy. In this study, a top-down progressive deepening method is developed fo...

Association rule mining algorithm is used to extract relevant information from database and transmit into simple and easiest form. Association rule mining is used in large set of data. It is used for mining frequent item sets in the database or in data warehouse. It is also one type of data mining procedure. In this paper some of the association rule mining algorithms such as apriori, partition...

We present a method that applies association rule mining for information retrieval. Our approach is different from traditional information retrieval since retrieval is done based on association rather than similarity, which might be useful for knowledge discovery purposes such as finding an explanation or elaboration for an event in a collection of domain-specific documents. The method proposed...

One of the best-known problems in data mining is association rule mining. It requires very large computation and I/O traffic capacity, therefore several distributed and parallel association rule mining algorithms have been developed. However the association rule mining problem is NP complete, the execution time estimation of the algorithms can be very important, especially for load balancing or...

A novel framework for mining temporal association rules by discovering itemsets with a genetic algorithm is introduced. Metaheuristics have been applied to association rule mining, we show the efficacy of extending this to another variant temporal association rule mining. Our framework is an enhancement to existing temporal association rule mining methods as it employs a genetic algorithm to si...

Software systems are expected to change over their lifetime in order to remain useful. Understanding a software system that has undergone changes is often difficult due to unavailability of up-to-date documentation. Under these circumstances, source code is the only reliable means of information regarding the system. In this paper, we apply data mining, or more specifically, association rule mi...

This research demonstrates the application of association rule mining to spatio-temporal data. Association rule mining seeks to discover associations among transactions encoded in a database. An association rule takes the form A → B where A (the antecedent) and B (the consequent) are sets of predicates. A spatio-temporal association rule occurs when there is a spatio-temporal relationship in th...