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Research about recommending books based on hierarchical analysis method and BP neural network

机译:基于层次分析法和BP神经网络的图书推荐研究

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摘要

At present, with the development of the information technologies and the internet, evaluation and, the recommendation of all kinds of information are increasingly concerned. According to the user behaviour information of a famous online bookstore, analysis of the factors affecting user ratings to establish user on the books of the scoring system model, and then the user recommended books. The original data is filtered first. The label, social friends, books browsing amount of three groups of data were analysed by bivariate correlation analysis respectively, so that we can get the number of users on the books, scores and label users' good friends, the history of the book number of pageviews a positive correlation. As to the second question, this paper established the AHP model and BP neural network model to predict the score. So we can obtain more accurate results by comparing the two kinds of model.
机译:当前,随着信息技术和互联网的发展,对各种信息的评估和推荐日益受到关注。根据某著名在线书店的用户行为信息,分析影响用户评价的因素,在评分系统模型的书本上建立用户,然后推荐用户。首先过滤原始数据。通过二元相关分析分别分析了三组数据的标签,社交朋友,图书浏览量,从而可以得到图书的用户数,得分和标签用户的好朋友,图书的历史记录。网页浏览量呈正相关。对于第二个问题,本文建立了AHP模型和BP神经网络模型来预测得分。因此,通过比较这两种模型,我们可以获得更准确的结果。

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