The application of matrix Apriori algorithm in web log mining
Hanxiao Zhang, Wei Guo Song, Lizhen Liu, Hanshi Wang · 2017
With the advent of the big data era, data mining technology has gradually become mature, association rules analysis is also applied in many fields. Web log mining is an important way to do some personalized services and achieve Web personalize. Apriori algorithm is a classical algorithm of association rules, but it has a lot of shortcomings. In recent years, the improvement about Apriori algorithm emerges in endlessly. In this paper, we mainly discuss the application of Matrix Apriori algorithm in Web log mining based on matrix storage. First, we analyze the improvements of Matrix Apriori and describe the process of the algorithm. We make some comparisons of several association rules algorithms. Then, Matrix Apriori algorithm is applied to Sogou search log and shoes website search log. Finally, according to the results of the Web log mining, we can make personalized recommendation and optimize site settings.