Traditional model of association rule mining is adapted to handle weighted association rule mining problems where each item is allowed to have a weight. The goal is to steer the mining focus to those significant relationships involving items with significant weights rather than being flooded in the combinatorial explosion of insignificant relationships. We discuss the use of association rules mining algorithm to push information automatically, and proposed mixed weighted association rules mining algorithm that apply to information push. We identify the related information set and the vertical weight through the analyzing of users' behavior, and use the Google's PageRank algorithm to define the horizontal weight of information. At last, we evaluate our algorithm against the traditional Apriori algorithm in information push, thereby justifying empirically the strength of our approach.
['Jike Ge', 'Yuhui Qiu', 'Zuqin Chen', 'Shiqun Yin']
Technology of Information Push Based on Weighted Association Rules Mining