Hybrid recommendation system oriented to local chronicles website

Abstract

The invention belongs to the technical field of website recommendation, and provides a hybrid recommendation system oriented to a local chronicles website. The hybrid recommendation system comprises a behavior recording module, a user classifying module and a user recommendation module; the behavior recording module is used for recording user registration information and behavior information and storing the user registration information and behavior information into a database; the user classifying module is used for dividing users into new users, general users and active users according to the local chronicles access frequency of the users, conducting feature analysis on each user class to select the suitable recommendation method to achieve personalized recommendation; the user recommendation module comprises TopN recommendation, association rule recommendation based on local chronicles labels and improvement and collaborative filtering recommendation based on the users. The system adopts different recommendation algorithms for users of different type according to the classifying result of the user classifying module. Personalized recommendation can be conducted according to different user types.

Description

technical field [0001] The invention belongs to the technical field of website recommendation, and in particular relates to a hybrid recommendation system for local chronicle websites. Background technique [0002] Local chronicles are an important carrier of Chinese traditional culture and contain rich information resources. As the relevant national departments put the digitization of local chronicles on the agenda, provinces across the country have successively established their own local chronicles websites. At present, a large number of users are using local chronicles websites to carry out study and research. However, when users are faced with a large amount of data information, it is difficult to find the information they are interested in. In this context, the personalized recommendation system has become one of the effective tools to solve the problem of information overload. At present, the most done in the field of local chronicles digitization technology is full-...

AI Technical Summary

Problems solved by technology

The recommendation based on local chronicles labels and improved association rules is mainly to solve the problem that the recommendation effect of collaborative filtering recommendation will gradually weaken when user data is sparse. On the other hand, the main task of association rule recommendation is to search for k-item frequent sets. If The amount of data is too large, which will reduce the performance of the system. In order to improve the performance of the system, the present invention only finds 2-item frequent sets and obtains strong association rules and combines local chronicles labels to obtain the final recommendation list