Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (23): 113-121.DOI: 10.3778/j.issn.1002-8331.2011-0350

• Big Data and Cloud Computing • Previous Articles     Next Articles

Diversified Recommendation Method Based on Similar Users’Curiosity

TIAN Wei’an, CHEN Hongmei, ZHOU Lihua   

  1. School of Information Science and Engineering, Yunnan University, Kunming 650504, China
  • Online:2021-12-01 Published:2021-12-02



  1. 云南大学 信息学院,昆明 650504


Recommendation technology has become the key technology to provide personalized services in the era of information overload. Since the diversity of recommendation results can improve the recommendation effect, the diversified recommendation method has attracted researcher’s attention. It is difficult to obtain the relationships between users, such as friends and trust, which is used in the existing method based on the curiosity of friends. So, this paper proposes a diversified recommendation method based on Similar Users’ Curiosity(SUC). First, it analyzes the users’ real ratings and calculates the set of similar users. Second, it calculates the users’ predicted ratings based on the collaborative filtering method. Then, it calculates the users’ curiosity ratings by analyzing the users’ real ratings and predicted ratings. Finally, it integrates the predicted ratings and curiosity ratings to calculate the users’ item recommendation lists. The proposed method is more useful because it does not require additional information. Experiments on five real data sets show that compared with the benchmark methods, the SUC method not only improves the diversity of recommendation, but also improves the accuracy, recall and coverage of recommendation.

Key words: recommendation system, collaborative filtering, similarity, curiosity, diversity



关键词: 推荐系统, 协同过滤, 相似度, 好奇心, 多样性