Journal of Shandong University(Engineering Science) ›› 2024, Vol. 54 ›› Issue (1): 45-51.doi: 10.6040/j.issn.1672-3961.0.2023.168

• Machine Learning & Data Mining • Previous Articles    

Adaptive label information learning for intention detection

MA Kun, LIU Xiaoyun, LI Leping, JI Ke, CHEN Zhenxiang, YANG Bo   

  1. School of Information Science and Engineering, University of Jinan, Jinan 250022, Shandong, China
  • Published:2024-02-01

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  • TP391
[1] LIU Jingzhou, CHANG Weicheng, WU Yuexin, et al. Deep learning for extreme multi-label text classification[C] //Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. Shinjuku, Tokyo, Japan: SIGIR, 2017: 115-124.
[2] LIANG Xiao, WANG Chenxu, ZHAO Guoshuai. Enhancing content marketing article detection with graph analysis[J]. IEEE Access, 2019, 7: 94869-94881.
[3] ZHANG Lu, ZHANG Jian, LI Zhibin, et al. Towards better graph representation: two-branch collaborative graph neural networks for multimodal marketing intention detection[C] //2020 IEEE International Conference on Multimedia and Expo. London, UK: IEEE, 2020: 1-6.
[4] MATHIAS N, MOHAMED A, KONSTANTIN K. Learning convolutional neural networks for graphs[C] //Proceedings of the 33nd International Conference on Machine Learning. New York, USA: JMLR, 2016: 2014-2023
[5] DANIEL B, GHOLAMREZA H, TREVOR C. Graph-to-sequence learning using gated graph neural networks[C] //Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics. Melbourne, Australia: ACL, 2018: 273-283.
[6] LIU Yuli, LIU Yiquan, ZHOU Ke, et al. Detecting promotion campaigns in query auto completion[C] //Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. New York, USA: ACM, 2016: 125-134.
[7] FAN Xiaoming, WANG Chenxu, LIANG Xiao. Extracting advertisements from content marketing articles based on topicCNN[C] //DASC/PiCom/CBD- Com/CyberSciTech. Calgary, Canada: IEEE, 2020: 355-360.
[8] YANG Pengcheng, SUN Xu, LI Wei, et al. SGM: sequence generation model for multi-label classification[C] //Proceedings of the 27th International Conference on Computational Linguistics. Santa Fe, New Mexico, USA: ACL, 2018: 3915-3926.
[9] LIU Jingzhou, CHANG Weicheng, WU Yuexin, et al. Deep learning for extreme multi-label text classification[C] //Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, USA: ACM, 2017: 115-124.
[10] ZHANG Wenjie, YAN Junchi, WANG Xiangfeng, et al. Deep extreme multi-label learning[C] //Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval. New York, USA: ACM, 2018: 100-107.
[11] DU Cunxiao, CHUN Zhaozheng, FENG Fuli, et al. Explicit interaction model towards text classification[C] //Proceedings of the AAAI Conference on Artificial Intelligence. Honolulu, USA: AAAI Press, 2019: 6359-6366.
[12] THARANGA D, GEEGANAGE K. Concept embedded topic modeling technique[C] //Companion Proceedings of the Web Conference 2018. Lyon, France: WWW, 2018: 831-835.
[13] BLEI D M, NG A Y, Jordan M I. Latent dirichlet allocation[J]. Journal of Machine Learning Research, 2003, 3: 993-1022.
[14] DEMBCZYNSKI K, WAEGEMAN W, CHENG W, et al. Regret analysis for performance metrics in multi-label classification: the case of hamming and subset zero-one loss[C] //Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Barcelona, Spain: Springer, 2010: 280-295.
[15] LACOSTE-JULIEN S, SHA F, JORDAN M. DiscLDA: discriminative learning for dimensionality reduction and classification[J]. Advances in Neural Information Processing Systems, 2008, 21: 897-904.
[16] RAMAGE D, HALL D, NALLAPATI R, et al. Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora[C] //Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Singapore: ACL, 2009: 248-256.
[17] YAO Liang, MAO Chengsheng, LUO Yuan. Graph convolutional networks for text classification[C] //Proceedings of the AAAI Conference on Artificial Intelligence. Honolulu, USA: AAAI Press, 2019: 7370-7377.
[18] HUANG Lianzhe, MA Dedong, LI Sujian, et al. Text level graph neural network for text classification[C] //Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Hong Kong, China: ACL, 2019: 3444-3450.
[19] FENG Yifan, YOU Haoxuan, ZHANG Zizhao, et al. Hypergraph neural networks[C] //Proceedings of the AAAI Conference on Artificial Intelligence. Honolulu, USA: AAAI Press, 2019: 3558-3565.
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