{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T20:22:27Z","timestamp":1775766147890,"version":"3.50.1"},"publisher-location":"New York, New York, USA","reference-count":54,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Technology of the People's Republic of China","award":["2015CB352403"],"award-info":[{"award-number":["2015CB352403"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1145\/3178876.3186175","type":"proceedings-article","created":{"date-parts":[[2018,4,13]],"date-time":"2018-04-13T15:53:48Z","timestamp":1523634828000},"page":"1835-1844","source":"Crossref","is-referenced-by-count":913,"title":["DKN"],"prefix":"10.1145","author":[{"given":"Hongwei","family":"Wang","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University & Microsoft Research Asia, Shanghai, China"}]},{"given":"Fuzheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}]},{"given":"Xing","family":"Xie","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}]},{"given":"Minyi","family":"Guo","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]}],"member":"320","reference":[{"key":"key-10.1145\/3178876.3186175-1","doi-asserted-by":"crossref","unstructured":"Deepak Agarwal and Bee-Chung Chen . 2009. Regression-based latent factor models. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 19--28.","DOI":"10.1145\/1557019.1557029"},{"key":"key-10.1145\/3178876.3186175-2","doi-asserted-by":"crossref","unstructured":"Trapit Bansal, Mrinal Das, and Chiranjib Bhattacharyya . 2015. Content driven user profiling for comment-worthy recommendations of news and blog articles Proceedings of the 9th ACM Conference on Recommender Systems. ACM.","DOI":"10.1145\/2792838.2800186"},{"key":"key-10.1145\/3178876.3186175-3","unstructured":"David M Blei, Andrew Y Ng, and Michael I Jordan . 2003. Latent dirichlet allocation. Journal of machine Learning research Vol. 3, Jan (2003), 993--1022."},{"key":"key-10.1145\/3178876.3186175-4","unstructured":"Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko . 2013. Translating embeddings for modeling multi-relational data Advances in Neural Information Processing Systems. 2787--2795."},{"key":"key-10.1145\/3178876.3186175-5","unstructured":"Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio, et almbox. . 2011. Learning Structured Embeddings of Knowledge Bases. AAAI, Vol. Vol. 6. 6."},{"key":"key-10.1145\/3178876.3186175-6","doi-asserted-by":"crossref","unstructured":"Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et almbox. . 2016. Wide &#38; deep learning for recommender systems. In Proceedings of the 1st Workshop on Deep Learning for Recommender Systems. ACM, 7--10.","DOI":"10.1145\/2988450.2988454"},{"key":"key-10.1145\/3178876.3186175-7","unstructured":"Alexis Conneau, Holger Schwenk, Lo\"&#305;c Barrault, and Yann Lecun . 2016. Very deep convolutional networks for natural language processing. arXiv preprint arXiv:1606.01781 (2016)."},{"key":"key-10.1145\/3178876.3186175-8","doi-asserted-by":"crossref","unstructured":"Paul Covington, Jay Adams, and Emre Sargin . 2016. Deep neural networks for youtube recommendations. Proceedings of the 10th ACM Conference on Recommender Systems. ACM, 191--198.","DOI":"10.1145\/2959100.2959190"},{"key":"key-10.1145\/3178876.3186175-9","unstructured":"Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J Smola, Jing Jiang, and Chong Wang . 2014. Jointly modeling aspects, ratings and sentiments for movie recommendation (jmars) KDD. ACM, 193--202."},{"key":"key-10.1145\/3178876.3186175-10","doi-asserted-by":"crossref","unstructured":"Li Dong, Furu Wei, Ming Zhou, and Ke Xu . 2015. Question Answering over Freebase with Multi-Column Convolutional Neural Networks. ACL (1).","DOI":"10.3115\/v1\/P15-1026"},{"key":"key-10.1145\/3178876.3186175-11","unstructured":"Ali Mamdouh Elkahky, Yang Song, and Xiaodong He . 2015. A multi-view deep learning approach for cross domain user modeling in recommendation systems Proceedings of the 24th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee, 278--288."},{"key":"key-10.1145\/3178876.3186175-12","unstructured":"Yanjie Fu, Bin Liu, Yong Ge, Zijun Yao, and Hui Xiong . 2014. User preference learning with multiple information fusion for restaurant recommendation Proceedings of the 2014 SIAM International Conference on Data Mining. SIAM."},{"key":"key-10.1145\/3178876.3186175-13","unstructured":"Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He . 2017. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Proceedings of the 26th International Joint Conference on Artificial Intelligence."},{"key":"key-10.1145\/3178876.3186175-14","unstructured":"Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua . 2017. Neural collaborative filtering. In WWW. International World Wide Web Conferences Steering Committee, 173--182."},{"key":"key-10.1145\/3178876.3186175-15","unstructured":"James Hong and Michael Fang . 2015. Sentiment analysis with deeply learned distributed representations of variable length texts. Technical Report. Technical report, Stanford University."},{"key":"key-10.1145\/3178876.3186175-16","unstructured":"Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck . 2013. Learning deep structured semantic models for web search using clickthrough data CIKM. ACM, 2333--2338."},{"key":"key-10.1145\/3178876.3186175-17","unstructured":"Rodolphe Jenatton, Nicolas L Roux, Antoine Bordes, and Guillaume R Obozinski . 2012. A latent factor model for highly multi-relational data Advances in Neural Information Processing Systems. 3167--3175."},{"key":"key-10.1145\/3178876.3186175-18","unstructured":"Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao . 2015. Knowledge Graph Embedding via Dynamic Mapping Matrix ACL. 687--696."},{"key":"key-10.1145\/3178876.3186175-19","doi-asserted-by":"crossref","unstructured":"Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom . 2014. A convolutional neural network for modelling sentences. arXiv preprint arXiv:1404.2188 (2014).","DOI":"10.3115\/v1\/P14-1062"},{"key":"key-10.1145\/3178876.3186175-20","doi-asserted-by":"crossref","unstructured":"Yoon Kim . 2014. Convolutional neural networks for sentence classification EMNLP.","DOI":"10.3115\/v1\/D14-1181"},{"key":"key-10.1145\/3178876.3186175-21","unstructured":"Diederik Kingma and Jimmy Ba . 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"key-10.1145\/3178876.3186175-22","doi-asserted-by":"crossref","unstructured":"Michal Kompan and M&#225;ria Bielikov&#225; . 2010. Content-Based News Recommendation. In EC-Web, Vol. Vol. 61. Springer, 61--72.","DOI":"10.1007\/978-3-642-15208-5_6"},{"key":"key-10.1145\/3178876.3186175-23","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton . 2012. Imagenet classification with deep convolutional neural networks Advances in neural information processing systems. 1097--1105."},{"key":"key-10.1145\/3178876.3186175-24","unstructured":"Siwei Lai, Liheng Xu, Kang Liu, and Jun Zhao . 2015. Recurrent Convolutional Neural Networks for Text Classification. AAAI, Vol. Vol. 333. 2267--2273."},{"key":"key-10.1145\/3178876.3186175-25","unstructured":"Lihong Li, Wei Chu, John Langford, and Robert E Schapire . 2010. A contextual-bandit approach to personalized news article recommendation Proceedings of the 19th international conference on World wide web. ACM, 661--670."},{"key":"key-10.1145\/3178876.3186175-26","unstructured":"Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu . 2015. Learning Entity and Relation Embeddings for Knowledge Graph Completion AAAI."},{"key":"key-10.1145\/3178876.3186175-27","unstructured":"Jiahui Liu, Peter Dolan, and Elin R&#248;nby Pedersen . 2010. Personalized news recommendation based on click behavior Proceedings of the 15th international conference on Intelligent user interfaces. ACM, 31--40."},{"key":"key-10.1145\/3178876.3186175-28","unstructured":"Tapio Luostarinen and Oskar Kohonen . 2013. Using topic models in content-based news recommender systems Proceedings of the 19th Nordic Conference of Computational Linguistics. Link&#246;ping University Electronic Press, 239--251."},{"key":"key-10.1145\/3178876.3186175-29","unstructured":"Yuanhua Lv, Taesup Moon, Pranam Kolari, Zhaohui Zheng, Xuanhui Wang, and Yi Chang . 2011. Learning to model relatedness for news recommendation Proceedings of the 20th international conference on World wide web. ACM, 57--66."},{"key":"key-10.1145\/3178876.3186175-30","unstructured":"Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean . 2013. Distributed representations of words and phrases and their compositionality Advances in neural information processing systems. 3111--3119."},{"key":"key-10.1145\/3178876.3186175-31","unstructured":"David Milne and Ian H Witten . 2008. Learning to link with wikipedia. In CIKM. ACM, 509--518."},{"key":"key-10.1145\/3178876.3186175-32","unstructured":"Shumpei Okura, Yukihiro Tagami, Shingo Ono, and Akira Tajima . 2017. Embedding-based News Recommendation for Millions of Users KDD. ACM, 1933--1942."},{"key":"key-10.1145\/3178876.3186175-33","doi-asserted-by":"crossref","unstructured":"Enrico Palumbo, Giuseppe Rizzo, and Rapha&#235;l Troncy . 2017. entity2rec: Learning User-Item Relatedness from Knowledge Graphs for Top-N Item Recommendation. (2017).","DOI":"10.1145\/3109859.3109889"},{"key":"key-10.1145\/3178876.3186175-34","doi-asserted-by":"crossref","unstructured":"Owen Phelan, Kevin McCarthy, and Barry Smyth . 2009. Using twitter to recommend real-time topical news. Proceedings of the third ACM conference on Recommender systems. ACM, 385--388.","DOI":"10.1145\/1639714.1639794"},{"key":"key-10.1145\/3178876.3186175-35","doi-asserted-by":"crossref","unstructured":"Steffen Rendle . 2012. Factorization machines with libfm. ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 3, 3 (2012), 57.","DOI":"10.1145\/2168752.2168771"},{"key":"key-10.1145\/3178876.3186175-36","unstructured":"Avirup Sil and Alexander Yates . 2013. Re-ranking for joint named-entity recognition and linking Proceedings of the 22nd ACM international conference on Conference on information &#38; knowledge management. ACM, 2369--2374."},{"key":"key-10.1145\/3178876.3186175-37","unstructured":"Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng . 2013 a. Reasoning with neural tensor networks for knowledge base completion Advances in neural information processing systems. 926--934."},{"key":"key-10.1145\/3178876.3186175-38","doi-asserted-by":"crossref","unstructured":"Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Ng, and Christopher Potts . 2013 b. Recursive deep models for semantic compositionality over a sentiment treebank Proceedings of the 2013 conference on empirical methods in natural language processing. 1631--1642.","DOI":"10.18653\/v1\/D13-1170"},{"key":"key-10.1145\/3178876.3186175-39","unstructured":"Jeong-Woo Son, A Kim, Seong-Bae Park, et almbox. . 2013. A location-based news article recommendation with explicit localized semantic analysis Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval. ACM, 293--302."},{"key":"key-10.1145\/3178876.3186175-40","unstructured":"Kai Sheng Tai, Richard Socher, and Christopher D Manning . 2015. Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:1503.00075 (2015)."},{"key":"key-10.1145\/3178876.3186175-41","unstructured":"Chong Wang and David M Blei . 2011. Collaborative topic modeling for recommending scientific articles Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 448--456."},{"key":"key-10.1145\/3178876.3186175-42","doi-asserted-by":"crossref","unstructured":"Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Weinan Zhang, Fuzheng Zhang, Xing Xie, and Minyi Guo . 2018 a. GraphGAN: Graph Representation Learning with Generative Adversarial Nets AAAI.","DOI":"10.1609\/aaai.v32i1.11872"},{"key":"key-10.1145\/3178876.3186175-43","unstructured":"Hongwei Wang, Jia Wang, Miao Zhao, Jiannong Cao, and Minyi Guo . 2017 b. Joint-Topic-Semantic-aware Social Recommendation for Online Voting Proceedings of the 26th ACM International Conference on Conference on Information and Knowledge Management. ACM, 347--356."},{"key":"key-10.1145\/3178876.3186175-44","unstructured":"Hao Wang, Naiyan Wang, and Dit-Yan Yeung . 2015. Collaborative deep learning for recommender systems Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 1235--1244."},{"key":"key-10.1145\/3178876.3186175-45","doi-asserted-by":"crossref","unstructured":"Hongwei Wang, Fuzheng Zhang, Min Hou, Xing Xie, Minyi Guo, and Qi Liu . 2018 b. Shine: Signed heterogeneous information network embedding for sentiment link prediction WSDM.","DOI":"10.1145\/3159652.3159666"},{"key":"key-10.1145\/3178876.3186175-46","doi-asserted-by":"crossref","unstructured":"Jin Wang, Zhongyuan Wang, Dawei Zhang, and Jun Yan . 2017 a. Combining Knowledge with Deep Convolutional Neural Networks for Short Text Classification Proceedings of the International Joint Conference on Artificial Intelligence.","DOI":"10.24963\/ijcai.2017\/406"},{"key":"key-10.1145\/3178876.3186175-47","doi-asserted-by":"crossref","unstructured":"Xuejian Wang, Lantao Yu, Kan Ren, Guanyu Tao, Weinan Zhang, Yong Yu, and Jun Wang . 2017 c. Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration. In KDD. ACM.","DOI":"10.1145\/3097983.3098096"},{"key":"key-10.1145\/3178876.3186175-48","doi-asserted-by":"crossref","unstructured":"Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen . 2014. Knowledge Graph Embedding by Translating on Hyperplanes AAAI. 1112--1119.","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"key-10.1145\/3178876.3186175-49","doi-asserted-by":"crossref","unstructured":"Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, and Tie-Yan Liu . 2014. Rc-net: A general framework for incorporating knowledge into word representations Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management. ACM, 1219--1228.","DOI":"10.1145\/2661829.2662038"},{"key":"key-10.1145\/3178876.3186175-50","unstructured":"Hong-Jian Xue, Xin-Yu Dai, Jianbing Zhang, Shujian Huang, and Jiajun Chen . 2017. Deep Matrix Factorization Models for Recommender Systems Proceedings of the 26th International Joint Conference on Artificial Intelligence."},{"key":"key-10.1145\/3178876.3186175-51","unstructured":"Bishan Yang and Tom Mitchell . 2017. Leveraging knowledge bases in lstms for improving machine reading Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Vol. Vol. 1."},{"key":"key-10.1145\/3178876.3186175-52","unstructured":"Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma . 2016. Collaborative knowledge base embedding for recommender systems KDD. ACM, 353--362."},{"key":"key-10.1145\/3178876.3186175-53","unstructured":"Xiang Zhang, Junbo Zhao, and Yann LeCun . 2015. Character-level convolutional networks for text classification NIPS. 649--657."},{"key":"key-10.1145\/3178876.3186175-54","doi-asserted-by":"crossref","unstructured":"Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Xiao Ma, Yanghui Yan, Xingya Dai, Han Zhu, Junqi Jin, Han Li, and Kun Gai . 2017. Deep Interest Network for Click-Through Rate Prediction. arXiv preprint arXiv:1706.06978 (2017).","DOI":"10.1145\/3219819.3219823"}],"event":{"name":"the 2018 World Wide Web Conference","location":"Lyon, France","acronym":"WWW '18","number":"2018","sponsor":["SIGWEB, ACM Special Interest Group on Hypertext, Hypermedia, and Web","IW3C2, International World Wide Web Conference Committee"],"start":{"date-parts":[[2018,4,23]]},"end":{"date-parts":[[2018,4,27]]}},"container-title":["Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3178876.3186175","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3186175&ftid=1957416&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T17:27:51Z","timestamp":1751563671000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3178876.3186175"}},"subtitle":["Deep Knowledge-Aware Network for News Recommendation"],"proceedings-subject":"World Wide Web","short-title":[],"issued":{"date-parts":[[2018]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1145\/3178876.3186175","relation":{},"subject":[],"published":{"date-parts":[[2018]]}}}