A Novel Time-Aware Hybrid Recommendation Scheme Combining User Feedback and Collaborative Filtering
A Novel Time-Aware Hybrid Recommendation Scheme Combining User Feedback and Collaborative Filtering
复制标题
一种结合用户反馈和协同过滤的新型时间感知混合推荐方案
DOI：
10.1155/2020/8896694
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发表时间：
2020-10-23
影响因子：
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通讯作者：
Han, Dezhi
中科院分区：
文献类型：
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作者：
Li, Hongzhi;Han, Dezhi
目前，推荐系统被广泛应用于各个领域，以解决信息过载的问题。协同过滤和基于内容的推荐系统是推荐系统中的代表性解决方案，然而基于内容的推荐模型存在推荐结果种类单一、缺乏对用户偏好的有效感知等缺点;而协同过滤模型存在冷启动问题，且其所采用的聚类算法对其影响较大。针对这些问题，本文提出了一种基于协同过滤和基于内容的混合推荐方案。在该方案中，我们提出了时间影响因子的概念，并在此基础上建立了具有时间感知的用户偏好模型，同时利用用户对推荐项的反馈来提高推荐模型的准确性。最后，提出的混合模型结合了内容推荐和协同过滤的逻辑回归算法的基础上的结果。
Nowadays, recommender systems are used widely in various fields to solve the problem of information overload. Collaborative filtering and content-based are representative solutions in recommender systems, however, the content-based model has some shortcomings, such as single kind of recommendation results, lack of effective perception of user preferences; while, for the collaborative filtering model, there is a cold start problem, and such a model is greatly affected by its adopted clustering algorithm. To address these issues, a hybrid recommendation scheme is proposed in this article, which is based on both collaborative filtering and content-based. In this scheme, we propose the concept of time impact factor, and a time-aware user preference model is built based on it. Also, user feedback on recommendation items is utilized to improve the accuracy of our proposed recommendation model. Finally, the proposed hybrid model combines the results of content recommendation and collaborative filtering based on the logistic regression algorithm.