标题:Deep multimodal network: A multi-signal input neural network for ad click predictions
作者:Chen, Yang ;Du, Guanglei ;Wang, Xu
作者机构:[Chen, Yang ;Du, Guanglei ;Wang, Xu ] Science and Technology on Parallel and Distributed Laboratory, National University of Defense Technology, Changs 更多
会议名称:2nd International Conference on Big Data Technologies, ICBDT 2019
会议日期:August 28, 2019 - August 30, 2019
来源:ACM International Conference Proceeding Series
出版年:2019
页码:165-170
DOI:10.1145/3358528.3358561
摘要:Online advertisement is an important source of revenue for internet companies, so increasing click-through rates (CTR) on ads is crucial. the traditional CTR prediction model only extracts the classification features and numerical features of the advertisement, but ignores the title, description and other text features of the advertisement. However, we know that such information is very important for an advertisement. Therefore, we propose a deep multimodal network (DMN) to solve this problem. on the basis of the traditional deep model, DMN add the text features of cyclic neural network learning, so as to improve the performance of the model. we also did a lot of visual data analysis on the dataset, Finally, we conducted a comparative experiment on the real-world dataset.
© 2019 Association for Computing Machinery.
收录类别:EI
资源类型:会议论文
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