{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T05:17:31Z","timestamp":1755926251540,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":43,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,10,17]],"date-time":"2018-10-17T00:00:00Z","timestamp":1539734400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,10,17]]},"DOI":"10.1145\/3269206.3271714","type":"proceedings-article","created":{"date-parts":[[2018,10,22]],"date-time":"2018-10-22T12:08:27Z","timestamp":1540210107000},"page":"517-526","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Adversarial Training Model Unifying Feature Driven and Point Process Perspectives for Event Popularity Prediction"],"prefix":"10.1145","author":[{"given":"Qitian","family":"Wu","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Chaoqi","family":"Yang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Hengrui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Xiaofeng","family":"Gao","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Paul","family":"Weng","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"given":"Guihai","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2018,10,17]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Andersen","author":"Abadi Mart\u00edn","year":"2016","unstructured":"Mart\u00edn Abadi and David G . Andersen . 2016 . Learning to Protect Communications with Adversarial Neural Cryptography. CoRR , Vol. abs\/ 1610 .06918 (2016). Mart\u00edn Abadi and David G. Andersen. 2016. Learning to Protect Communications with Adversarial Neural Cryptography. CoRR , Vol. abs\/1610.06918 (2016)."},{"key":"e_1_3_2_1_2_1","volume-title":"Towards Principled Methods for Training Generative Adversarial Networks. CoRR","author":"Arjovsky Mart\u00edn","year":"2017","unstructured":"Mart\u00edn Arjovsky and L\u00e9 on Bottou . 2017. Towards Principled Methods for Training Generative Adversarial Networks. CoRR , Vol. abs\/ 1701 .04862 ( 2017 ). Mart\u00edn Arjovsky and L\u00e9 on Bottou. 2017. Towards Principled Methods for Training Generative Adversarial Networks. CoRR , Vol. abs\/1701.04862 (2017)."},{"key":"e_1_3_2_1_3_1","unstructured":"Mart\u00edn Arjovsky Soumith Chintala and L\u00e9 on Bottou. 2017. Wasserstein Generative Adversarial Networks. In ICML. 214--223.  Mart\u00edn Arjovsky Soumith Chintala and L\u00e9 on Bottou. 2017. Wasserstein Generative Adversarial Networks. In ICML. 214--223."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2740908.2742744"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2567997"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939852"},{"key":"e_1_3_2_1_7_1","volume-title":"An Introduction to the Theory of Point Processes","author":"Daley D.J.","year":"2007","unstructured":"D.J. Daley and David Vere-Jones . 2007. An Introduction to the Theory of Point Processes . Springer ( 2007 ). D.J. Daley and David Vere-Jones. 2007. An Introduction to the Theory of Point Processes. Springer (2007)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939875"},{"key":"e_1_3_2_1_9_1","volume-title":"COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. In NIPS. 1954--1962.","author":"Farajtabar Mehrdad","year":"2015","unstructured":"Mehrdad Farajtabar , Yichen Wang , Manuel Gomez-Rodriguez , Shuang Li , Hongyuan Zha , and Le Song . 2015 . COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. In NIPS. 1954--1962. Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha, and Le Song. 2015. COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. In NIPS. 1954--1962."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2567948.2577312"},{"key":"e_1_3_2_1_11_1","unstructured":"Manuel Gomez-Rodriguez Jure Leskovec and Bernhard Sch\u00f6 lkopf. 2013. Modeling Information Propagation with Survival Theory. In ICML. 666--674.   Manuel Gomez-Rodriguez Jure Leskovec and Bernhard Sch\u00f6 lkopf. 2013. Modeling Information Propagation with Survival Theory. In ICML. 666--674."},{"key":"e_1_3_2_1_12_1","unstructured":"Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron C. Courville and Yoshua Bengio. 2014. Generative Adversarial Nets. In NIPS. 2672--2680.   Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron C. Courville and Yoshua Bengio. 2014. Generative Adversarial Nets. In NIPS. 2672--2680."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.137"},{"key":"e_1_3_2_1_14_1","volume-title":"Courville","author":"Gulrajani Ishaan","year":"2017","unstructured":"Ishaan Gulrajani , Faruk Ahmed , Mart\u00edn Arjovsky , Vincent Dumoulin , and Aaron C . Courville . 2017 . Improved Training of Wasserstein GANs. In NIPS. 5769--5779. Ishaan Gulrajani, Faruk Ahmed, Mart\u00edn Arjovsky, Vincent Dumoulin, and Aaron C. Courville. 2017. Improved Training of Wasserstein GANs. In NIPS. 5769--5779."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2661829.2662012"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609476"},{"key":"e_1_3_2_1_17_1","volume-title":"Alan Ritter, and Dan Jurafsky.","author":"Li Jiwei","year":"2017","unstructured":"Jiwei Li , Will Monroe , Tianlin Shi , S\u00e9 bastien Jean , Alan Ritter, and Dan Jurafsky. 2017 b. Adversarial Learning for Neural Dialogue Generation. In EMNLP . 2157--2169. Jiwei Li, Will Monroe, Tianlin Shi, S\u00e9 bastien Jean, Alan Ritter, and Dan Jurafsky. 2017b. Adversarial Learning for Neural Dialogue Generation. In EMNLP . 2157--2169."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132883"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132911"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132997"},{"key":"e_1_3_2_1_21_1","volume-title":"BEEP: A Bayesian Perspective Early Stage Event Prediction Model for Online Social Networks. In ICDM. 973--978.","author":"Ma Xiao","year":"2017","unstructured":"Xiao Ma , Xiaofeng Gao , and Guihai Chen . 2017 a. BEEP: A Bayesian Perspective Early Stage Event Prediction Model for Online Social Networks. In ICDM. 973--978. Xiao Ma, Xiaofeng Gao, and Guihai Chen. 2017a. BEEP: A Bayesian Perspective Early Stage Event Prediction Model for Online Social Networks. In ICDM. 973--978."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983812"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1981.1056305"},{"key":"e_1_3_2_1_24_1","unstructured":"Sasa Petrovic Miles Osborne and Victor Lavrenko. 2011. RT to Win! Predicting Message Propagation in Twitter. In ICWSM .  Sasa Petrovic Miles Osborne and Victor Lavrenko. 2011. RT to Win! Predicting Message Propagation in Twitter. In ICWSM ."},{"key":"e_1_3_2_1_25_1","unstructured":"Scott E. Reed Zeynep Akata Xinchen Yan Lajanugen Logeswaran Bernt Schiele and Honglak Lee. 2016. Generative Adversarial Text to Image Synthesis. In ICML. 1060--1069.   Scott E. Reed Zeynep Akata Xinchen Yan Lajanugen Logeswaran Bernt Schiele and Honglak Lee. 2016. Generative Adversarial Text to Image Synthesis. In ICML. 1060--1069."},{"key":"e_1_3_2_1_26_1","volume-title":"A Tutorial on Hawkes Processes for Events in Social Media. CoRR","author":"Rizoiu Marian-Andrei","year":"2017","unstructured":"Marian-Andrei Rizoiu , Young Lee , Swapnil Mishra , and Lexing Xie . 2017. A Tutorial on Hawkes Processes for Events in Social Media. CoRR , Vol. abs\/ 1708 .06401 ( 2017 ). Marian-Andrei Rizoiu, Young Lee, Swapnil Mishra, and Lexing Xie. 2017. A Tutorial on Hawkes Processes for Events in Social Media. CoRR , Vol. abs\/1708.06401 (2017)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186108"},{"key":"e_1_3_2_1_28_1","unstructured":"Tim Salimans Ian J. Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved Techniques for Training GANs. In NIPS. 2226--2234.   Tim Salimans Ian J. Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved Techniques for Training GANs. In NIPS. 2226--2234."},{"key":"e_1_3_2_1_29_1","volume-title":"LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity. In IJCAI. 2679--2685.","author":"Samanta Bidisha","year":"2017","unstructured":"Bidisha Samanta , Abir De , Abhijnan Chakraborty , and Niloy Ganguly . 2017 . LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity. In IJCAI. 2679--2685. Bidisha Samanta, Abir De, Abhijnan Chakraborty, and Niloy Ganguly. 2017. LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity. In IJCAI. 2679--2685."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Hua-Wei Shen Dashun Wang Chaoming Song and Albert-L\u00e1 szl\u00f3 Barab\u00e1 si. 2014. Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes. In AAAI . 291--297.   Hua-Wei Shen Dashun Wang Chaoming Song and Albert-L\u00e1 szl\u00f3 Barab\u00e1 si. 2014. Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes. In AAAI . 291--297.","DOI":"10.1609\/aaai.v28i1.8739"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Benjamin Shulman Amit Sharma and Dan Cosley. 2016. Predictability of Popularity: Gaps between Prediction and Understanding. In ICWSM . 348--357.  Benjamin Shulman Amit Sharma and Dan Cosley. 2016. Predictability of Popularity: Gaps between Prediction and Understanding. In ICWSM . 348--357.","DOI":"10.1609\/icwsm.v10i1.14748"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/SocialCom.2010.33"},{"key":"e_1_3_2_1_33_1","volume-title":"Le","author":"Sutskever Ilya","year":"2014","unstructured":"Ilya Sutskever , Oriol Vinyals , and Quoc V . Le . 2014 . Sequence to Sequence Learning with Neural Networks. In NIPS. 3104--3112. Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014. Sequence to Sequence Learning with Neural Networks. In NIPS. 3104--3112."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806556"},{"key":"e_1_3_2_1_35_1","unstructured":"Duy Quang Vu Arthur U. Asuncion David R. Hunter and Padhraic Smyth. 2011. Dynamic Egocentric Models for Citation Networks. In ICML. 857--864.   Duy Quang Vu Arthur U. Asuncion David R. Hunter and Padhraic Smyth. 2011. Dynamic Egocentric Models for Citation Networks. In ICML. 857--864."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080786"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098067"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3014812.3014813"},{"key":"e_1_3_2_1_39_1","unstructured":"Shuai Xiao Mehrdad Farajtabar Xiaojing Ye Junchi Yan Xiaokang Yang Le Song and Hongyuan Zha. 2017a. Wasserstein Learning of Deep Generative Point Process Models. In NIPS . 3250--3259.  Shuai Xiao Mehrdad Farajtabar Xiaojing Ye Junchi Yan Xiaokang Yang Le Song and Hongyuan Zha. 2017a. Wasserstein Learning of Deep Generative Point Process Models. In NIPS . 3250--3259."},{"key":"e_1_3_2_1_40_1","volume-title":"Chu","author":"Xiao Shuai","year":"2017","unstructured":"Shuai Xiao , Junchi Yan , Xiaokang Yang , Hongyuan Zha , and Stephen M . Chu . 2017 b. Modeling the Intensity Function of Point Process Via Recurrent Neural Networks. In AAAI . 1597--1603. Shuai Xiao, Junchi Yan, Xiaokang Yang, Hongyuan Zha, and Stephen M. Chu. 2017b. Modeling the Intensity Function of Point Process Via Recurrent Neural Networks. In AAAI . 1597--1603."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Jiang Yang and Scott Counts. 2010. Predicting the Speed Scale and Range of Information Diffusion in Twitter. In ICWSM .  Jiang Yang and Scott Counts. 2010. Predicting the Speed Scale and Range of Information Diffusion in Twitter. In ICWSM .","DOI":"10.1609\/icwsm.v4i1.14039"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.79"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783401"}],"event":{"name":"CIKM '18: The 27th ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Torino Italy","acronym":"CIKM '18"},"container-title":["Proceedings of the 27th ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3269206.3271714","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3269206.3271714","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:44:28Z","timestamp":1750207468000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3269206.3271714"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,17]]},"references-count":43,"alternative-id":["10.1145\/3269206.3271714","10.1145\/3269206"],"URL":"https:\/\/doi.org\/10.1145\/3269206.3271714","relation":{},"subject":[],"published":{"date-parts":[[2018,10,17]]},"assertion":[{"value":"2018-10-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}