The Study Of Association Rule And Utility Pattern Mining Algorithm

With the coming of the age of information, more and more companies and government agencies are being digitally equipped. And the database technology is playing more important a role than ever before. Huge amount of information remains undiscovered in these accumulated databases .it becomes a crucial challenge to efficiently and correctly extract the useful information hidden in these databases .data mining technology address this problem. As far as it goes , the most popular technology in data mining is association rules mining. Many researches have been contributed in this area.The mostly studied association rule mining model care about whether an item is included in a transaction or not. And thus treat all items equally. While in the real world case, there are discriminations between items. We can quantify these differences between items , one option is that we can use utility as a measure to signify the usefulness of the respective items.The thesis works on the research of association rule mining, along with the research on utility pattern mining, which is a emergent new topic in the data mining community .utility pattern mining is somewhat like the association rule and the sequence analysis ,for they share the same form of the targeted database .and all contrived to obtain the finding of potentially useful, non-trivial ,decision-support knowledge.The thesis proposes a association mining algorithm based on partition and decomposition. The algorithm was grounded on the idea of partitioning the whole database which is a way to save for RAM storage .it scans the database once and shrinks the amount of candidate item-sets. The experiment concludes that it has an edge in the efficiency comparison.Another contribution of the thesis is the study on the utility pattern mining. the author proposed an heuristic algorithm based the dynamic binary partition tree. The algorithm doing so by further assuming the problem in an optimization framework .the experiment also shows that it is more robust than former ones.This dissertation paper mainly deal with the research of association rule mining and the utility item-sets mining problem. the experiment dedicated to the verification of the proposed algorithms show that the research is novel and constructive .