Level wise Search Algorithm Based on Action and Non-Action Type Data to Find Irregular Association Rules
Razan Paul, Abu Sayed Md. Latiful Hoque
Journal of E-Technology, Vol. 2, No. 1, 2011.
DOI: 
Link: http://www.dline.info/jet/fulltext/v2n1/5.pdf
Abstract:
Conventional positive association rules are frequently occuring patterns. The patterns represent what decisions are routinely made based on a set of facts. Irregular association rules are the patterns that represent what decisions are rarely made based on the same set of facts. The application domains by nature require the irregular association rules and hence we developed a level wise search algorithm that works based on action and non-action type data to find irregular association rules. Action type and non-action type will enable to discover irregular association rules. The algorithms that can tap the irregular associations have potential and our algorithm is found to be more effective in a real world datasets drawn in the health care field.