{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T17:11:51Z","timestamp":1778346711811,"version":"3.51.4"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Ministry of Education Humanities and Social Science Project","award":["22YJC740110"],"award-info":[{"award-number":["22YJC740110"]}]},{"name":"the Social Science Planning Foundation of Liaoning Province","award":["L21CXW003"],"award-info":[{"award-number":["L21CXW003"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1007\/s10489-024-05326-z","type":"journal-article","created":{"date-parts":[[2024,2,15]],"date-time":"2024-02-15T13:03:17Z","timestamp":1708002197000},"page":"2703-2715","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Emotion-cause pair extraction via knowledge-driven multi-classification and graph-based position embedding"],"prefix":"10.1007","volume":"54","author":[{"given":"Linlin","family":"Zong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinglin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahui","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianchao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5453-978X","authenticated-orcid":false,"given":"Bo","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,15]]},"reference":[{"key":"5326_CR1","unstructured":"Chen Y, Lee SYM, Li S, Huang CR (2010) Emotion cause detection with linguistic constructions. In: Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), pp. 179\u2013187"},{"issue":"5","key":"5326_CR2","first-page":"1691","volume":"14","author":"J Liu","year":"2023","unstructured":"Liu J (2023) Application and research of computer aided technology in clothing design driven by emotional elements. International Journal of System Assurance Engineering and Management 14(5):1691\u20131702","journal-title":"International Journal of System Assurance Engineering and Management"},{"issue":"1","key":"5326_CR3","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1504\/IJMEI.2022.119314","volume":"14","author":"V Gupta","year":"2022","unstructured":"Gupta V, Mittal M, Mittal V, Gupta A (2022) An efficient AR modelling-based electrocardiogram signal analysis for health informatics. International Journal of Medical Engineering and Informatics 14(1):74\u201389","journal-title":"International Journal of Medical Engineering and Informatics"},{"key":"5326_CR4","doi-asserted-by":"crossref","unstructured":"Xia R, Ding Z (2019) Emotion-cause pair extraction: A new task to emotion analysis in texts. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 1003\u20131012","DOI":"10.18653\/v1\/P19-1096"},{"key":"5326_CR5","doi-asserted-by":"crossref","unstructured":"Ding Z, Xia R, Yu J (2020) Ecpe-2d: Emotion-cause pair extraction based on joint two-dimensional representation, interaction and prediction. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3161\u20133170","DOI":"10.18653\/v1\/2020.acl-main.288"},{"issue":"4","key":"5326_CR6","doi-asserted-by":"publisher","first-page":"1743","DOI":"10.1109\/TAFFC.2022.3206960","volume":"13","author":"W Cao","year":"2022","unstructured":"Cao W, Zhang K, Ruan S, Tao H, Zhao S, Wang H, Liu Q, Chen E (2022) Causal narrative comprehension: A new perspective for emotion cause extraction. IEEE Transactions on Affective Computing 13(4):1743\u20131758","journal-title":"IEEE Transactions on Affective Computing"},{"issue":"4","key":"5326_CR7","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1145\/3558548","volume":"41","author":"Z Cheng","year":"2023","unstructured":"Cheng Z, Jiang Z, Yin Y, Wang C, Ge S, Gu Q (2023) A consistent dual-mrc framework for emotion-cause pair extraction. ACM Transactions on Information Systems 41(4):105\u2013110527","journal-title":"ACM Transactions on Information Systems"},{"key":"5326_CR8","doi-asserted-by":"publisher","first-page":"1266","DOI":"10.1162\/tacl_a_00518","volume":"10","author":"H Yanaka","year":"2022","unstructured":"Yanaka H, Mineshima K (2022) Compositional evaluation on japanese textual entailment and similarity. Transactions of the Association for Computational Linguistics 10:1266\u20131284","journal-title":"Transactions of the Association for Computational Linguistics"},{"issue":"1","key":"5326_CR9","doi-asserted-by":"publisher","first-page":"929","DOI":"10.3233\/JIFS-223275","volume":"45","author":"SN Reshmi","year":"2023","unstructured":"Reshmi SN, Shreelekshmi R (2023) Textual entailment classification using syntactic structures and semantic relations. Journal of Intelligent and Fuzzy Systems 45(1):929\u2013939","journal-title":"Journal of Intelligent and Fuzzy Systems"},{"key":"5326_CR10","doi-asserted-by":"crossref","unstructured":"Verma D, Lal YK, Sinha S, Durme BV, Poliak A (2023) Evaluating paraphrastic robustness in textual entailment models. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 880\u2013892","DOI":"10.18653\/v1\/2023.acl-short.76"},{"key":"5326_CR11","unstructured":"Lee SYM, Chen Y, Huang CR (2010) A text-driven rule-based system for emotion cause detection. In: Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pp. 45\u201353"},{"issue":"3","key":"5326_CR12","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1111\/j.1467-8640.2012.00459.x","volume":"29","author":"SYM Lee","year":"2013","unstructured":"Lee SYM, Chen Y, Huang CR, Li S (2013) Detecting emotion causes with a linguistic rule-based approach 1. Computational Intelligence 29(3):390\u2013416","journal-title":"Computational Intelligence"},{"issue":"4","key":"5326_CR13","doi-asserted-by":"publisher","first-page":"1742","DOI":"10.1016\/j.eswa.2013.08.073","volume":"41","author":"W Li","year":"2014","unstructured":"Li W, Xu H (2014) Text-based emotion classification using emotion cause extraction. Expert Systems with Applications 41(4):1742\u20131749","journal-title":"Expert Systems with Applications"},{"key":"5326_CR14","doi-asserted-by":"crossref","unstructured":"Yada S, Ikeda K, Hoashi K, Kageura K (2017) A bootstrap method for automatic rule acquisition on emotion cause extraction. In: 2017 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 414\u2013421. IEEE","DOI":"10.1109\/ICDMW.2017.60"},{"key":"5326_CR15","doi-asserted-by":"crossref","unstructured":"Gui L, Yuan L, Xu R, Liu B, Lu Q, Zhou Y (2014) Emotion cause detection with linguistic construction in chinese weibo text. In: CCF International Conference on Natural Language Processing and Chinese Computing, pp. 457\u2013464","DOI":"10.1007\/978-3-662-45924-9_42"},{"key":"5326_CR16","doi-asserted-by":"crossref","unstructured":"Song S, Meng Y (2015) Detecting concept-level emotion cause in microblogging. In: Proceedings of the 24th International Conference on World Wide Web, pp. 119\u2013120","DOI":"10.1145\/2740908.2742710"},{"issue":"1","key":"5326_CR17","first-page":"1","volume":"17","author":"X Cheng","year":"2017","unstructured":"Cheng X, Chen Y, Cheng B, Li S, Zhou G (2017) An emotion cause corpus for chinese microblogs with multiple-user structures. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) 17(1):1\u201319","journal-title":"ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)"},{"key":"5326_CR18","doi-asserted-by":"crossref","unstructured":"Gui L, Wu D, Xu R, Lu Q, Zhou Y (2016) Event-driven emotion cause extraction with corpus construction. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing","DOI":"10.18653\/v1\/D16-1170"},{"key":"5326_CR19","doi-asserted-by":"publisher","first-page":"6343","DOI":"10.1609\/aaai.v33i01.33016343","volume":"33","author":"Z Ding","year":"2019","unstructured":"Ding Z, He H, Zhang M, Xia R (2019) From independent prediction to reordered prediction: Integrating relative position and global label information to emotion cause identification. Proceedings of the AAAI Conference on Artificial Intelligence 33:6343\u20136350","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"5326_CR20","doi-asserted-by":"crossref","unstructured":"Gui L, Hu J, He Y, Xu R, Lu Q, Du J (2017) A question answering approach for emotion cause extraction. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 1593\u20131602","DOI":"10.18653\/v1\/D17-1167"},{"issue":"6","key":"5326_CR21","doi-asserted-by":"publisher","first-page":"646","DOI":"10.23919\/TST.2017.8195347","volume":"22","author":"R Xu","year":"2017","unstructured":"Xu R, Hu J, Lu Q, Wu D, Gui L (2017) An ensemble approach for emotion cause detection with event extraction and multi-kernel svms. Tsinghua Science and Technology 22(6):646\u2013659","journal-title":"Tsinghua Science and Technology"},{"key":"5326_CR22","doi-asserted-by":"crossref","unstructured":"Li X, Song K, Feng S, Wang D, Zhang Y (2018) A co-attention neural network model for emotion cause analysis with emotional context awareness. In:Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4752\u20134757","DOI":"10.18653\/v1\/D18-1506"},{"key":"5326_CR23","doi-asserted-by":"crossref","unstructured":"Fan C, Yan H, Du J, Gui L, Bing L, Yang M, Xu R, Mao R (2019) A knowledge regularized hierarchical approach for emotion cause analysis. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP IJCNLP), pp. 5618\u20135628","DOI":"10.18653\/v1\/D19-1563"},{"issue":"3","key":"5326_CR24","doi-asserted-by":"publisher","first-page":"1779","DOI":"10.1109\/TAFFC.2022.3218648","volume":"14","author":"X Chen","year":"2023","unstructured":"Chen X, Li Q, Li Z, Xie H, Wang FL, Wang J (2023) A reinforcement learning based two-stage model for emotion cause pair extraction. IEEE Transactions on Affective Computing 14(3):1779\u20131790","journal-title":"IEEE Transactions on Affective Computing"},{"key":"5326_CR25","doi-asserted-by":"crossref","unstructured":"Fan C, Yuan C, Du J, Gui L, Yang M, Xu R (2020) Transition-based directed graph construction for emotion-cause pair extraction. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3707\u20133717","DOI":"10.18653\/v1\/2020.acl-main.342"},{"key":"5326_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126252","volume":"543","author":"S Chen","year":"2023","unstructured":"Chen S, Mao K (2023) A graph attention network utilizing multi-granular information for emotion-cause pair extraction. Neurocomputing 543:126252","journal-title":"Neurocomputing"},{"key":"5326_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110703","volume":"278","author":"M Li","year":"2023","unstructured":"Li M, Zhao H, Gu T, Ying D (2023) Experiencer-driven and knowledge-aware graph model for emotion-cause pair extraction. Knowledge-Based Systems 278:110703","journal-title":"Knowledge-Based Systems"},{"key":"5326_CR28","doi-asserted-by":"publisher","first-page":"2779","DOI":"10.1109\/TASLP.2021.3102194","volume":"29","author":"Z Cheng","year":"2021","unstructured":"Cheng Z, Jiang Z, Yin Y, Li N, Gu Q (2021) A unified target-oriented sequence-to-sequence model for emotion-cause pair extraction. IEEE\/ACM Transactions on Audio, Speech, and Language Processing 29:2779\u20132791","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"key":"5326_CR29","doi-asserted-by":"crossref","unstructured":"Chen F, Shi Z, Yang Z, Huang Y (2022) Recurrent synchronization network for emotion-cause pair extraction. Knowledge-Based Systems 238:107965","DOI":"10.1016\/j.knosys.2021.107965"},{"key":"5326_CR30","doi-asserted-by":"crossref","unstructured":"Ding Z, Xia R, Yu J (2020) End-to-end emotion-cause pair extraction based on sliding window multi-label learning. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 3574\u20133583","DOI":"10.18653\/v1\/2020.emnlp-main.290"},{"key":"5326_CR31","doi-asserted-by":"crossref","unstructured":"Chen Y, Hou W, Li S, Wu C, Zhang X (2020) End-to-end emotion-cause pair extraction with graph convolutional network. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 198\u2013207","DOI":"10.18653\/v1\/2020.coling-main.17"},{"key":"5326_CR32","doi-asserted-by":"crossref","unstructured":"Wei P, Zhao J, Mao W (2020) Effective inter-clause modeling for end-to-end emotion-cause pair extraction. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3171\u20133181","DOI":"10.18653\/v1\/2020.acl-main.289"},{"key":"5326_CR33","doi-asserted-by":"crossref","unstructured":"Liu M, Shi J, Cao K, Zhu J, Liu S (2018) Analyzing the training processes of deep generative models. IEEE Transactions on Visualization and Computer Graphics 24(1):77\u201387","DOI":"10.1109\/TVCG.2017.2744938"},{"key":"5326_CR34","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.neucom.2020.03.105","volume":"409","author":"H Tang","year":"2020","unstructured":"Tang H, Ji D, Zhou Q (2020) Joint multi-level attentional model for emotion detection and emotion-cause pair extraction. Neurocomputing 409:329\u2013340","journal-title":"Neurocomputing"},{"key":"5326_CR35","unstructured":"Singh A, Hingane S, Wani S, Modi A (2021) An end-to-end network for emotion cause pair extraction. In: Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pp. 84\u201391"},{"key":"5326_CR36","doi-asserted-by":"crossref","unstructured":"Chen X, Li Q, Wang J (2020) A unified sequence labeling model for emotion cause pair extraction. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 208\u2013218","DOI":"10.18653\/v1\/2020.coling-main.18"},{"issue":"9","key":"5326_CR37","doi-asserted-by":"publisher","first-page":"10548","DOI":"10.1007\/s10489-022-03873-x","volume":"53","author":"W Huang","year":"2023","unstructured":"Huang W, Yang Y, Huang X, Peng Z, Xiong L (2023) Emotion-cause pair extraction based on interactive attention. Applied Intelligence 53(9):10548\u201310558","journal-title":"Applied Intelligence"},{"key":"5326_CR38","doi-asserted-by":"publisher","unstructured":"Yu J, Liu W, He Y, Zhang C (2021) A mutually auxiliary multitask model with self-distillation for emotion-cause pair extraction. IEEE Access 9:26811\u201326821. https:\/\/doi.org\/10.1109\/ACCESS.2021.3057880","DOI":"10.1109\/ACCESS.2021.3057880"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05326-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05326-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05326-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T20:45:12Z","timestamp":1710362712000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05326-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":38,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,2]]}},"alternative-id":["5326"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05326-z","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]},"assertion":[{"value":"5 February 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 February 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.The authors declare the following financial interests\/personal relationships which may be considered as potential competing interests:","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}},{"value":"In our study, we utilized publicly available anonymized datasets to conduct our research. As a result, no additional ethical considerations were deemed necessary.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical and informed consent for data used"}}]}}