The Research And Application Of Fuzzy Association Rules In Recommendation Information System

Along with the development of information industrialization, we need accept the more and more information. However, we cannot accept and understand those information. The tread is so damaging to life, learn, job and interpersonal relationship.The requiring drives the technology development, so the recommendation system had grown. The recommendation system locates and push some information we interested.The personalized recommendation system collects some important details, and develops and maintains a user model and the user love hobby, so it can predict the knowledge which we interested and recommend and the potential or valuable information.The association rule mines all frequent item sets from the history data, and finds all the frequent item sets. So far, the association rule has been the way of recommendation we always use. However, the association rule under the Boolean type has too many limitations, and the way does not consider him fuzziness of men’s thought, which leads the result of deviation. So, we introduce the fuzzy concept into the association rules, and the rationality of the results will be greatly improved in the recommendation system. At the same time, there is a disadvantage of association rules,which is using a large set of frequent candidate sets, which affects the efficiency of the algorithm. So, in this paper, the fuzzy association rules based on the decision tree are proposed, and it is applied to the recommendation system. This not only improves the efficiency of the algorithm, but also to make the recommendation system with personalized and humane.Based on the background of recommendation system, this paper takes the association rules as the main line, takes the fuzzy theory and the decision tree as the main points, and emphatically introduces the principle and application of the algorithm.The main contents are as follows:1) The basic principles of association rules and fuzzy association rules are studied,and the process of mining frequent sets of apriority algorithm is introduced, and the process of mining strong association rules is introduced.2) The basic principle of decision tree algorithm is studied, and the process of constructing decision tree using ID3 algorithm and C4.5 algorithm is introduced.3) Research on the algorithm of fuzzy association rules based on decision tree, and emphatically introduces how to optimize the performance of apriority algorithm.4) The fuzzy association rules and fuzzy association rules based on decision tree to the recommendation system, and programming, in the practical application for the difference of two models.In the demand driven, the use of the recommended methods to build the recommended system, to achieve the personalized recommendation system and personalized, is conducive to our life and learning.