Traffic safety is an important part of the roadway in sustainable development. Freeway traffic crashes typically cause serious casualties and property losses, being a threat to public safety. Figuring out potential correlation between various risk factors revealing their coupling mechanisms are effective ways explore identity freeway crash causes. However, existing association rule mining algor...

Association Rule is an important tool for today data mining technique. But this work only concern with positive rule generation till now. This paper gives study for generating negative and positive rule generation as demand of modern data mining techniques requirements. Here also gives detail of “A method for generating all positive and negative Association Rules” (PNAR). PNAR help to generates...

This paper deals with the effective utilization of association rule mining algorithms in large databases used for especially business organizations where the amount of transactions and items plays a crucial role for decision making. Frequent item-set generation and the creation of strong association rules from the frequent item-set patterns are the two basic steps in association rule mining. We...

In this paper, the problem of constraint-based pattern discovery is investigated. By allowing more user-specified constraints other than traditional rule measurements, e.g., minimum support and minimum confidence, research work on this topic endeavoured to reflect real interest of analysts and relieve them from the overabundance of rules. Surprisingly, very little research has been conducted to...

Web usage mining refers to the automatic discovery and analysis of patterns in click stream and associated data collected or generated as a result of user interactions with web resources on one or more web sites. It consists of three phases which are data Preprocessing, pattern discovery and pattern analysis. In the pattern discovery phase, frequent pattern discovery algorithms applied on raw d...

In this paper, we use transaction data as the source data of mining, and each transaction data contains a consumer ever buy items. We mine association rules from two aspects. One is to present a Boolean FP-tree algorithm to mine association rules with the Boolean computation according to the FP-tree algorithm and CDAR algorithm. The experiments show that the performances of our algorithm are fa...

Association rule mining is one of the most popular data mining methods. However, mining association rules often results in a very large number of found rules, leaving the analyst with the task to go through all the rules and discover interesting ones. In this paper, we present the performance comparison of Apriori and FP-growth algorithms. The performance is analyzed based on the execution time...