Library book intelligent recommendation system based on artificial intelligence

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-04-23 DOI:10.3233/JIFS-189934
L. Pang
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引用次数: 1

Abstract

In order to improve the accuracy of intelligent recommendation of library books, an intelligent recommendation system of library books based on artificial intelligence was designed. The system uses artificial intelligence technology to clean up and normalize the data, automatically extracts the user’s historical evaluation data of books, divides the whole user space into several similar user clusters through the similar user clustering module, constructs the user book evaluation matrix according to the historical evaluation data, and uses the hybrid collaborative filtering algorithm which integrates user based and project-based to predict each user a book evaluation matrix of similar user clusters was used to realize the intelligent recommendation of library books, and the recommendation results were displayed to users through the user interface module. The results show that the average absolute error and root mean square error of the system are always the lowest, and the recommendation accuracy is high. When the control parameter is 0.4, the best intelligent book recommendation effect can be obtained; the recommended recall rate is not affected by the sparse density of the data set, and the stability is strong.
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基于人工智能的图书馆图书智能推荐系统
为了提高图书智能推荐的准确性,设计了一种基于人工智能的图书智能推荐系统。系统利用人工智能技术对数据进行清理和规范化,自动提取用户对图书的历史评价数据,通过相似用户聚类模块将整个用户空间划分为几个相似的用户簇,根据历史评价数据构建用户图书评价矩阵;并采用基于用户和基于项目相结合的混合协同过滤算法对每个用户进行预测,利用相似用户群的图书评价矩阵实现图书馆图书的智能推荐,并通过用户界面模块将推荐结果显示给用户。结果表明,该系统的平均绝对误差和均方根误差始终最低,推荐精度较高。当控制参数为0.4时,智能图书推荐效果最佳;推荐召回率不受数据集稀疏密度的影响,稳定性强。
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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