Online museum information resource systems are getting popular these days which allow the users to get detailed information about the objects of their interest, and the user preferences are stored to search for related artifacts considering his/her online behavior. The behavior of users browsing online is integrated to capture relevant information which is integrated into museum information resources. Unfortunately, present implementations have errors in integration and optimization system, so a wireless network-based museum user behavior information integration system is proposed to calculate the user’s interest in museum’s cultural relics. The user behavior information resource model is developed based upon the degree of user interest, and forgetting functions with different decay rates are employed to describe changes in the interest level. This information is then used to construct users’ interest matrices. This matrix also contains information regarding the cultural relics that users have not yet visited. The system will introduce the interest weights of feature words to take the top features of the user behavior information for the integration of the users’ behavior and to combine the feature vectors that can represent the overall trajectory. Moreover, those feature vectors are described that can represent the local trajectory into feature vector to identify the slow-moving sparse targets, which is then utilized for the integration of users’ behavior information. The simulation tests prove that the proposed method can achieve low error in the integration process of user behavior information resources, thereby yielding good results.
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