基于面部表情识别的图书馆智能图书推荐系统

Yizhu Zhao, Jun Zeng
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引用次数: 2

摘要

为了解决信息过载的问题,推荐系统在各个领域得到了发展。面对形式多样、图书质量丰富的图书,基于多种推荐方法的图书推荐系统在图书馆得到了应用。传统的图书推荐系统存在推荐模式单一、缺乏针对性、推荐图书过于集中等问题。为了解决这些问题,本文提出了一种个性化的图书推荐系统。通过用户表情识别获取用户偏好,根据用户偏好向用户推荐图书。人脸表情识别采用卷积神经网络模型实现。这种推荐方法具有实时性和真实性。基于面部表情识别的图书推荐系统应用于图书馆机器人,可以提高用户的使用感。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Library Intelligent Book Recommendation System Using Facial Expression Recognition
To solve the problem of information overload, the recommendation system has developed in various fields. Faced with a variety of forms and rich masses of books, the book recommendation system based on various recommendation methods is applied in the library. In the traditional book recommendation system, there are some problems, such as single recommendation mode, lack of pertinence, too centralized recommended books and so on. In order to solve these problems, this paper proposes a personalized book recommendation system. Through user expression recognition to obtain user preferences, according to user preferences to recommend books to user. Facial expression recognition is realized by using convolution neural network model. This kind of recommendation method has real-time and authenticity. The book recommendation system based on facial expression recognition can improve users' sense of use when applied to library robots.
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