Shumpei Okura
ABSTRACT
It is necessary to understand the content of articles and user preferences to make effective news recommendations. While ID-based methods, such as collaborative filtering and low-rank factorization, are well known for making recommendations, they are not suitable for news recommendations because candidate articles expire quickly and are replaced with new ones within short spans of time. Word-based methods, which are often used in information retrieval settings, are good candidates in terms of system performance but have issues such as their ability to cope with synonyms and orthographical variants and define "queries" from users' historical activities. This paper proposes an embedding-based method to use distributed representations in a three step end-to-end manner: (i) start with distributed representations of articles based on a variant of a denoising autoencoder, (ii) generate user representations by using a recurrent neural network (RNN) with browsing histories as input sequences, and (iii) match and list articles for users based on inner-product operations by taking system performance into consideration. The proposed method performed well in an experimental offline evaluation using past access data on Yahoo! JAPAN's homepage. We implemented it on our actual news distribution system based on these experimental results and compared its online performance with a method that was conventionally incorporated into the system. As a result, the click-through rate (CTR) improved by 23% and the total duration improved by 10%, compared with the conventionally incorporated method. Services that incorporated the method we propose are already open to all users and provide recommendations to over ten million individual users per day who make billions of accesses per month.
- Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. Google Scholar
Cross Ref
- Henriette Cramer. 2015. Effects of Ad Quality & Content-Relevance on Perceived Content Quality Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems.Google Scholar
- Abhinandan S. Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram 2007. Google News Personalization: Scalable Online Collaborative Filtering Proceedings of the 16th International Conference on World Wide Web.Google ScholarDigital Library
- Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin 2008. LIBLINEAR: A library for large linear classification. The Journal of Machine Learning Research (2008).Google Scholar
- Sepp Hochreiter. 1991. Untersuchungen zu dynamischen neuronalen Netzen. Diploma thesis. bibinfoschoolInstitut für Informatik, Lehrstuhl Prof. Brauer, Technische Universit"at München.Google Scholar
- Sepp Hochreiter and Jürgen Schmidhuber 1997. Long short-term memory. Neural computation (1997).Google Scholar
- Thorsten Joachims. 2002. Optimizing Search Engines Using Clickthrough Data. Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Google ScholarDigital Library
- Rafal Jozefowicz, Wojciech Zaremba, and Ilya Sutskever. 2015. An empirical exploration of recurrent network architectures Proceedings of the 32nd International Conference on Machine Learning.Google Scholar
- Andrej Karpathy and Li Fei-Fei 2015. Deep visual-semantic alignments for generating image descriptions Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Google Scholar
- Mounia Lalmas, Janette Lehmann, Guy Shaked, Fabrizio Silvestri, and Gabriele Tolomei 2015. Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.Google Scholar
- Quoc Le and Tomas Mikolov 2014. Distributed Representations of Sentences and Documents Proceedings of The 31st International Conference on Machine Learning.Google Scholar
- Shumpei Okura, Yukihiro Tagami, and Akira Tajima. 2016. Article De-duplication Using Distributed Representations Proceedings of the 25th International Conference Companion on World Wide Web.Google Scholar
- Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. 2014. On the difficulty of training recurrent neural networks Proceedings of The 30th International Conference on Machine Learning.Google Scholar
- Jay Adams Paul Covington and Emre Sargin 2016. Deep Neural Networks for YouTube Recommendations. Proceedings of the 10th ACM Conference on Recommender Systems. New York, NY, USA.Google ScholarDigital Library
- Tara N Sainath, Oriol Vinyals, Andrew Senior, and Hasim Sak 2015. Convolutional, long short-term memory, fully connected deep neural networks Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on.Google ScholarCross Ref
- Tobias Schnabel, Igor Labutov, David Mimno, and Thorsten Joachims 2015. Evaluation methods for unsupervised word embeddings Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing.Google Scholar
- Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014. Sequence to Sequence Learning with Neural Networks Proceedings of Advances in Neural Information Processing Systems 27.Google Scholar
- Yukihiro Tagami, Hayato Kobayashi, Shingo Ono, and Akira Tajima 2015. Modeling User Activities on the Web Using Paragraph Vector Proceedings of the 24th International Conference on World Wide Web.Google Scholar
- Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol 2008. Extracting and composing robust features with denoising autoencoders Proceedings of the 25th international conference on Machine learning.Google Scholar
- Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol. 2010. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. The Journal of Machine Learning Research (2010).Google Scholar
- Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, and Tie-Yan Liu. 2014. Sequential click prediction for sponsored search with recurrent neural networks Proceedings of the 28th AAAI Conference on Artificial Intelligence.Google Scholar
- Erheng Zhong, Nathan Liu, Yue Shi, and Suju Rajan. 2015. Building Discriminative User Profiles for Large-scale Content Recommendation Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. endthebibliographyGoogle Scholar
Index Terms
- Embedding-based News Recommendation for Millions of Users
Recommendations
Personalized news recommendation based on click behavior
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