{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T15:42:34Z","timestamp":1774021354082,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["112-2221-E-006 -157 -MY3;112-2218-E-035 -001"],"award-info":[{"award-number":["112-2221-E-006 -157 -MY3;112-2218-E-035 -001"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3612843","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:27:40Z","timestamp":1698391660000},"page":"9451-9455","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Gradient Boost Tree Network based on Extensive Feature Analysis for Popularity Prediction of Social Posts"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2083-4438","authenticated-orcid":false,"given":"Chih-Chung","family":"Hsu","sequence":"first","affiliation":[{"name":"National Cheng Kung University, Tainan, Taiwan Roc"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6027-3083","authenticated-orcid":false,"given":"Chia-Ming","family":"Lee","sequence":"additional","affiliation":[{"name":"National Cheng Kung University, Tainan, Taiwan Roc"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4020-1767","authenticated-orcid":false,"given":"Xiu-Yu","family":"Hou","sequence":"additional","affiliation":[{"name":"National Cheng Kung University, Tainan, Taiwan Roc"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8298-3230","authenticated-orcid":false,"given":"Chi-Han","family":"Tsai","sequence":"additional","affiliation":[{"name":"National Cheng Kung University, NEED, Taiwan Roc"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3551568"},{"key":"e_1_3_2_1_3_1","volume-title":"Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi.","author":"Dai Wenliang","year":"2023","unstructured":"Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi. 2023. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning. arxiv: 2305.06500 [cs.CV]"},{"key":"e_1_3_2_1_4_1","volume-title":"EVA-02: A Visual Representation for Neon Genesis. arXiv preprint arXiv:2303.11331","author":"Fang Yuxin","year":"2023","unstructured":"Yuxin Fang, Quan Sun, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao. 2023. EVA-02: A Visual Representation for Neon Genesis. arXiv preprint arXiv:2303.11331 (2023)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1080\/14786440109462720"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3356064"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3266443"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3551593"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3417332"},{"key":"e_1_3_2_1_10_1","volume-title":"Lightgbm: A highly efficient gradient boosting decision tree. In Advances in Neural Information Processing Systems. 3146--3154.","author":"Ke Guolin","year":"2017","unstructured":"Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu. 2017. Lightgbm: A highly efficient gradient boosting decision tree. In Advances in Neural Information Processing Systems. 3146--3154."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3416273"},{"key":"e_1_3_2_1_12_1","first-page":"18","article-title":"Classification and regression by randomForest","volume":"2","author":"Liaw Andy","year":"2002","unstructured":"Andy Liaw, Matthew Wiener, et al. 2002. Classification and regression by randomForest. R News, Vol. 2, 3 (2002), 18--22.","journal-title":"R News"},{"key":"e_1_3_2_1_13_1","volume-title":"Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692 (2019)."},{"key":"e_1_3_2_1_14_1","volume-title":"Raziur Rahman, Souparno Ghosh, and Ranadip Pal.","author":"Matlock Kevin","year":"2018","unstructured":"Kevin Matlock, Carlos De Niz, Raziur Rahman, Souparno Ghosh, and Ranadip Pal. 2018. Investigation of model stacking for drug sensitivity prediction. BMC bioinformatics, Vol. 19, 3 (2018), 21--33."},{"key":"e_1_3_2_1_15_1","volume-title":"Anna Veronika Dorogush, and Andrey Gulin","author":"Prokhorenkova Liudmila","year":"2018","unstructured":"Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, and Andrey Gulin. 2018. CatBoost: unbiased boosting with categorical features. Advances in neural information processing systems, Vol. 31 (2018)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.365"},{"key":"e_1_3_2_1_18_1","volume-title":"TabNet: Attentive Interpretable Tabular Learning. arXiv:1908.07442","author":"Arik Tomas Pfister","year":"2019","unstructured":"Tomas Pfister Sercan O. Arik. 2019. TabNet: Attentive Interpretable Tabular Learning. arXiv:1908.07442 (2019)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3551607"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","unstructured":"Ross Wightman. 2019. PyTorch Image Models. https:\/\/github.com\/huggingface\/pytorch-image-models. https:\/\/doi.org\/10.5281\/zenodo.4414861","DOI":"10.5281\/zenodo.4414861"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3356084"},{"key":"e_1_3_2_1_22_1","volume-title":"Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks. In International Joint Conference on Artificial Intelligence (IJCAI)","author":"Wu Bo","year":"2017","unstructured":"Bo Wu, Wen-Huang Cheng, Yongdong Zhang, Huang Qiushi, Li Jintao, and Tao Mei. 2017. Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks. In International Joint Conference on Artificial Intelligence (IJCAI) (Melbourne, Australia)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9970"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3551576"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-1694(01)00594-7"}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","location":"Ottawa ON Canada","acronym":"MM '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3612843","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3612843","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:11:11Z","timestamp":1755821471000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3612843"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":25,"alternative-id":["10.1145\/3581783.3612843","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3612843","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}