Research of distributed data mining association rules model based on similarity

With the rapid development of social information, the application of distributed database system is increasing. Distributed data mining will play an important role in data mining, because distributed database system is different from centralized database system. We need to develop special algorithm for data mining on distributed database. Although current algorithms of association rules based on apriori have been optimized to a certain extend, we still have more work to do to increase its efficiency. This paper analyzes and introduces the algorithm for mining distributed association rules, and puts forward a new method for distributed data mining based on similarity which takes the heterogenous data source well into account. Finally the experiment also proves the increased veracity of this model.