{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:24:15Z","timestamp":1750220655364,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,19]],"date-time":"2020-10-19T00:00:00Z","timestamp":1603065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Project 'Learning Representations from Network Data' sponsored by Intel Technology India Pvt. Ltd."},{"name":"Central Sector Scheme of Pandit Madan Mohan Malaviya National Mission on Teachers & Teaching (PMMMNMTT) of MHRD Govt. of India"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,19]]},"DOI":"10.1145\/3340531.3412025","type":"proceedings-article","created":{"date-parts":[[2020,10,19]],"date-time":"2020-10-19T06:32:45Z","timestamp":1603089165000},"page":"1335-1344","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["A GAN-based Framework for Modeling Hashtag Popularity Dynamics Using Assistive Information"],"prefix":"10.1145","author":[{"given":"Avirup","family":"Saha","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Kharagpur, India, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niloy","family":"Ganguly","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Kharagpur, India, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,10,19]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Peng Bao Hua-Wei Shen Xiaolong Jin and Xue-Qi Cheng. 2015. Modeling and Predicting Popularity Dynamics of Microblogs using Self-Excited Hawkes Processes. In WWW.  Peng Bao Hua-Wei Shen Xiaolong Jin and Xue-Qi Cheng. 2015. Modeling and Predicting Popularity Dynamics of Microblogs using Self-Excited Hawkes Processes. In WWW.","DOI":"10.1145\/2740908.2742744"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Simon Bourigault Cedric Lagnier Sylvain Lamprier Ludovic Denoyer and Patrick Gallinari. 2014. Learning Social Network Embeddings for Predicting Information Diffusion. In WSDM.  Simon Bourigault Cedric Lagnier Sylvain Lamprier Ludovic Denoyer and Patrick Gallinari. 2014. Learning Social Network Embeddings for Predicting Information Diffusion. In WSDM.","DOI":"10.1145\/2556195.2556216"},{"key":"e_1_3_2_2_3_1","unstructured":"Daryl J Daley and David Vere-Jones. 2007. An introduction to the theory of point processes: volume II: general theory and structure .Springer Science & Business Media.  Daryl J Daley and David Vere-Jones. 2007. An introduction to the theory of point processes: volume II: general theory and structure .Springer Science & Business Media."},{"key":"e_1_3_2_2_4_1","unstructured":"Abir De Sourangshu Bhattacharya Parantapa Bhattacharya Niloy Ganguly and Soumen Chakrabarti. 2014. Learning a linear influence model from transient opinion dynamics. In CIKM.  Abir De Sourangshu Bhattacharya Parantapa Bhattacharya Niloy Ganguly and Soumen Chakrabarti. 2014. Learning a linear influence model from transient opinion dynamics. In CIKM."},{"key":"e_1_3_2_2_5_1","unstructured":"Abir De Isabel Valera Niloy Ganguly Sourangshu Bhattacharya and Manuel Gomez Rodriguez. 2016. Learning and forecasting opinion dynamics in social networks. In NIPS.  Abir De Isabel Valera Niloy Ganguly Sourangshu Bhattacharya and Manuel Gomez Rodriguez. 2016. Learning and forecasting opinion dynamics in social networks. In NIPS."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939875"},{"key":"e_1_3_2_2_7_1","volume-title":"Caetano Traina Jr, and Christos Faloutsos.","author":"Costa Alceu Ferraz","year":"2015","unstructured":"Alceu Ferraz Costa , Yuto Yamaguchi , Agma Juci Machado Traina , Caetano Traina Jr, and Christos Faloutsos. 2015 . Rsc : Mining and modeling temporal activity in social media. In KDD. Alceu Ferraz Costa, Yuto Yamaguchi, Agma Juci Machado Traina, Caetano Traina Jr, and Christos Faloutsos. 2015. Rsc: Mining and modeling temporal activity in social media. In KDD."},{"key":"e_1_3_2_2_8_1","unstructured":"M. Gomez-Rodriguez D. Balduzzi and B. Sch\u00f6lkopf. 2011. Uncovering the Temporal Dynamics of Diffusion Networks. In ICML.  M. Gomez-Rodriguez D. Balduzzi and B. Sch\u00f6lkopf. 2011. Uncovering the Temporal Dynamics of Diffusion Networks. In ICML."},{"key":"e_1_3_2_2_9_1","unstructured":"Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NIPS.  Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NIPS."},{"key":"e_1_3_2_2_10_1","volume-title":"Long short-term memory. Neural computation","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber . 1997. Long short-term memory. Neural computation , Vol. 9 , 8 ( 1997 ), 1735--1780. Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation, Vol. 9, 8 (1997), 1735--1780."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"crossref","unstructured":"Shen Hua-Wei Dashun Wang Chaoming Song and Albert Barabasi. 2014. Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes. In AAAI.  Shen Hua-Wei Dashun Wang Chaoming Song and Albert Barabasi. 2014. Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes. In AAAI.","DOI":"10.1609\/aaai.v28i1.8739"},{"key":"e_1_3_2_2_12_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_2_13_1","unstructured":"Shuang Li Shuai Xiao Shixiang Zhu Nan Du Yao Xie and Le Song. 2018. Learning Temporal Point Processes via Reinforcement Learning. In Advances in Neural Information Processing Systems. 10804--10814.  Shuang Li Shuai Xiao Shixiang Zhu Nan Du Yao Xie and Le Song. 2018. Learning Temporal Point Processes via Reinforcement Learning. In Advances in Neural Information Processing Systems. 10804--10814."},{"key":"e_1_3_2_2_14_1","unstructured":"Hongyuan Mei and Jason M Eisner. 2017. The neural hawkes process: A neurally self-modulating multivariate point process. In Advances in Neural Information Processing Systems. 6754--6764.  Hongyuan Mei and Jason M Eisner. 2017. The neural hawkes process: A neurally self-modulating multivariate point process. In Advances in Neural Information Processing Systems. 6754--6764."},{"key":"e_1_3_2_2_15_1","volume-title":"A focused backpropagation algorithm for temporal. Backpropagation: Theory, architectures, and applications","author":"Mozer Michael C","year":"1995","unstructured":"Michael C Mozer . 1995. A focused backpropagation algorithm for temporal. Backpropagation: Theory, architectures, and applications , Vol. 137 ( 1995 ). Michael C Mozer. 1995. A focused backpropagation algorithm for temporal. Backpropagation: Theory, architectures, and applications, Vol. 137 (1995)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Nir Rosenfeld Mor Nitzan and Amir Globerson. 2016. Discriminative learning of infection models. In WSDM.  Nir Rosenfeld Mor Nitzan and Amir Globerson. 2016. Discriminative learning of infection models. In WSDM.","DOI":"10.1145\/2835776.2835802"},{"key":"e_1_3_2_2_17_1","volume-title":"Learning Network Traffic Dynamics Using Temporal Point Process. In IEEE INFOCOM 2019-IEEE Conference on Computer Communications. IEEE","author":"Saha Avirup","year":"2019","unstructured":"Avirup Saha , Niloy Ganguly , Sandip Chakraborty , and Abir De . 2019 . Learning Network Traffic Dynamics Using Temporal Point Process. In IEEE INFOCOM 2019-IEEE Conference on Computer Communications. IEEE , 1927--1935. Avirup Saha, Niloy Ganguly, Sandip Chakraborty, and Abir De. 2019. Learning Network Traffic Dynamics Using Temporal Point Process. In IEEE INFOCOM 2019-IEEE Conference on Computer Communications. IEEE, 1927--1935."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271726"},{"key":"e_1_3_2_2_19_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_2_20_1","unstructured":"Bichen Shi Georgiana Ifrim and Neil Hurley. 2016. Learning-to-rank for real-time high-precision hashtag recommendation for streaming news. In WWW.  Bichen Shi Georgiana Ifrim and Neil Hurley. 2016. Learning-to-rank for real-time high-precision hashtag recommendation for streaming news. In WWW."},{"key":"e_1_3_2_2_21_1","unstructured":"Utkarsh Upadhyay Abir De and Manuel Gomez Rodriguez. 2018. Deep reinforcement learning of marked temporal point processes. In Advances in Neural Information Processing Systems. 3168--3178.  Utkarsh Upadhyay Abir De and Manuel Gomez Rodriguez. 2018. Deep reinforcement learning of marked temporal point processes. In Advances in Neural Information Processing Systems. 3168--3178."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271714"},{"key":"e_1_3_2_2_23_1","unstructured":"Shuai Xiao Mehrdad Farajtabar Xiaojing Ye Junchi Yan Xiaokang Yang Le Song and Hongyuan Zha. 2017. Wasserstein Learning of Deep Generative Point Process Models. In Advances in Neural Information Processing Systems. 3250--3259.  Shuai Xiao Mehrdad Farajtabar Xiaojing Ye Junchi Yan Xiaokang Yang Le Song and Hongyuan Zha. 2017. Wasserstein Learning of Deep Generative Point Process Models. In Advances in Neural Information Processing Systems. 3250--3259."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12072"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783401"}],"event":{"name":"CIKM '20: The 29th 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":"Virtual Event Ireland","acronym":"CIKM '20"},"container-title":["Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3340531.3412025","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3340531.3412025","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:02:29Z","timestamp":1750197749000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3340531.3412025"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,19]]},"references-count":25,"alternative-id":["10.1145\/3340531.3412025","10.1145\/3340531"],"URL":"https:\/\/doi.org\/10.1145\/3340531.3412025","relation":{},"subject":[],"published":{"date-parts":[[2020,10,19]]},"assertion":[{"value":"2020-10-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}