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Multi-Feature Fusion Book Recommendation Model Based on Deep Neural Network
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作者 Zhaomin Liang Tingting Liang 《Computer Systems Science & Engineering》 SCIE EI 2023年第10期205-219,共15页
The traditional recommendation algorithm represented by the collaborative filtering algorithm is the most classical and widely recommended algorithm in the practical industry.Most book recommendation systems also use ... The traditional recommendation algorithm represented by the collaborative filtering algorithm is the most classical and widely recommended algorithm in the practical industry.Most book recommendation systems also use this algorithm.However,the traditional recommendation algorithm represented by the collaborative filtering algorithm cannot deal with the data sparsity well.This algorithm only uses the shallow feature design of the interaction between readers and books,so it fails to achieve the high-level abstract learning of the relevant attribute features of readers and books,leading to a decline in recommendation performance.Given the above problems,this study uses deep learning technology to model readers’book borrowing probability.It builds a recommendation system model through themulti-layer neural network and inputs the features extracted from readers and books into the network,and then profoundly integrates the features of readers and books through the multi-layer neural network.The hidden deep interaction between readers and books is explored accordingly.Thus,the quality of book recommendation performance will be significantly improved.In the experiment,the evaluation indexes ofHR@10,MRR,andNDCGof the deep neural network recommendation model constructed in this paper are higher than those of the traditional recommendation algorithm,which verifies the effectiveness of the model in the book recommendation. 展开更多
关键词 book recommendation deep learning neural network multi-feature fusion personalized prediction
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Recommended Books
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《Research in Cold and Arid Regions》 2009年第1期98-98,共1页
Book 1: (Editor-in-Chief: Shi Yafeng; Published by Elsevier and Science Press Beijing in 2008, 539 pages) Glaciers and Related Environments in China Since the professional institution for glaciology attached to the Ch... Book 1: (Editor-in-Chief: Shi Yafeng; Published by Elsevier and Science Press Beijing in 2008, 539 pages) Glaciers and Related Environments in China Since the professional institution for glaciology attached to the Chinese Academy of Sciences was established in 1958, studies of glaciers in alpine regions, and of Quaternary glaciations throughout 展开更多
关键词 Recommended books book
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Research and implementation of a personalized book recommendation algorithm --Taking the library of Jinan University as an example
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作者 LI Tianzhang ZHU Yijia XIAO Liping 《International English Education Research》 2018年第3期20-22,共3页
Abstract: Taking the basic data and the log data of the various businesses of the automation integrated management system of the library in Jinan University as the research object this paper analyzes the internal rel... Abstract: Taking the basic data and the log data of the various businesses of the automation integrated management system of the library in Jinan University as the research object this paper analyzes the internal relationship between books and between the books and the readers, and designs a personalized book recommendation algorithm, the BookSimValue, on the basis of the user collaborative filteringtechnology. The experimental results show that the recommended book information produced by this algorithm can effectively help the readers to solve the problem of the book information overload, which can bring great convenience to the readers and effectively save the time of the readers' selection of the books, thus effectively improving the utilization of the library resources and the service levels. 展开更多
关键词 Recommendation system book recommendation: personalized recommendation algorithm
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