基于深度学习的广告邮件推荐研究
首发时间:2020-01-15
摘要:邮箱作为人们日常生活中的一个重要场景,是很好的进行广告投放的平台,但目前的广告邮件投放大多是无差异的。为了在降低广告主投放成本的同时,提高用户对广告邮件的兴趣度,本文针对邮箱使用场景进行了广告邮件个性化推荐的研究,基于用户行为数据对LSTM网络进行了优化。同时,收集整理了某邮箱的用户数据集,利用该数据集对所提出的模型进行了训练和测试。实验结果表明,本文提出的方法在邮箱平台上具有优越性。
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Advertising email recommendation based on deep learning
Abstract:Mailbox, as an important scene in people\'s daily life, is a good platform for advertising, but most of the current advertising has no difference between different people. In order to reduce the advertising cost of advertisers and improve users\' interest in advertising mail, this paper conducted a research on the personalized and accurate recommendation of advertising mail in the use scenario of mailbox, and optimized the LSTM network based on the user behavior data. At the same time, this paper collected the user data set of a mailbox, and the proposed model is trained and tested with the data set. The experimental results show that the proposed method is superior on the mailbox platform.
Keywords: Artificial intelligence Deep learning Recommendation system mailbox advertising mail
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基于深度学习的广告邮件推荐研究
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