An Event Detection Platform to Detect Gender Using Deep Learning
作者： Abdulrahman Aldhaheri , Je Lee , Khaled Almgren
DOI: 10.1109/UEMCON51285.2020.9298104
关键词:
摘要: There are many events that occur in e-commerce platforms, which can be used to detect and understand the behavior of online users. Behavior analyses users utilized impact both customers businesses. analysis seeks find useful information from clickstreams, address challenging problems. Clickstreams quantify users’ movements based on items they click an website. This work aims mine clickstreams predict genders. The proposed approach utilizes deep learning has been tested a real-world dataset; outperformed others terms accuracy.
sci-hub.st 参考文章(30)
Arjun Mukherjee, Bing Liu, Improving Gender Classification of Blog Authors empirical methods in natural language processing. pp. 207- 217 ,(2010)
Diederik P. Kingma, Jimmy Ba, Adam: A Method for Stochastic Optimization arXiv: Learning. ,(2014)
Gil Levi, Tal Hassncer, Age and gender classification using convolutional neural networks computer vision and pattern recognition. pp. 34- 42 ,(2015) , 10.1109/CVPRW.2015.7301352
Paul Thomas, Using Interaction Data to Explain Difficulty Navigating Online ACM Transactions on The Web. ,vol. 8, pp. 24- ,(2014) , 10.1145/2656343
Claudia Peersman, Walter Daelemans, Leona Van Vaerenbergh, Predicting age and gender in online social networks Proceedings of the 3rd international workshop on Search and mining user-generated contents - SMUC '11. pp. 37- 44 ,(2011) , 10.1145/2065023.2065035
Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov, Scalable Object Detection Using Deep Neural Networks computer vision and pattern recognition. pp. 2155- 2162 ,(2014) , 10.1109/CVPR.2014.276
Li Deng, Geoffrey Hinton, Brian Kingsbury, New types of deep neural network learning for speech recognition and related applications: an overview international conference on acoustics, speech, and signal processing. pp. 8599- 8603 ,(2013) , 10.1109/ICASSP.2013.6639344
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Andreas Müller, Joel Nothman, Gilles Louppe, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Édouard Duchesnay, Scikit-learn: Machine Learning in Python Journal of Machine Learning Research. ,vol. 12, pp. 2825- 2830 ,(2011)
Thompson S.H. Teo, To buy or not to buy online: adopters and non-adopters of online shopping in Singapore Behaviour & Information Technology. ,vol. 25, pp. 497- 509 ,(2006) , 10.1080/01449290500256155
B. Moghaddam, Ming-Hsuan Yang, Gender classification with support vector machines ieee international conference on automatic face and gesture recognition. pp. 306- 311 ,(2000) , 10.1109/AFGR.2000.840651