{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:44:11Z","timestamp":1760132651397,"version":"3.37.3"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T00:00:00Z","timestamp":1627257600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T00:00:00Z","timestamp":1627257600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2019YFB1405200"],"award-info":[{"award-number":["2019YFB1405200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"crossref","award":["61976015","61976016","61876198","61370130"],"award-info":[{"award-number":["61976015","61976016","61876198","61370130"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s10489-021-02683-x","type":"journal-article","created":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T21:02:41Z","timestamp":1627333361000},"page":"4663-4673","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Modeling semantic and emotional relationship in multi-turn emotional conversations using multi-task learning"],"prefix":"10.1007","volume":"52","author":[{"given":"Fuwei","family":"Cui","sequence":"first","affiliation":[]},{"given":"Hui","family":"Di","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Kazushige","family":"Ouchi","sequence":"additional","affiliation":[]},{"given":"Ze","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0170-626X","authenticated-orcid":false,"given":"Jinan","family":"Xu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,26]]},"reference":[{"issue":"4","key":"2683_CR1","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1109\/TNNLS.2020.2985588","volume":"32","author":"F Cui","year":"2021","unstructured":"Cui F, Cui Q, Song Y (2021) A survey on Learning-Based approaches for modeling and classification of Human\u2013Machine dialog systems. IEEE Trans Neural Netw Learn Syst 32(4):1418\u20131432. https:\/\/doi.org\/10.1109\/TNNLS.2020.2985588","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2683_CR2","doi-asserted-by":"crossref","unstructured":"Partala T, Surakka V (2004) The effects of affective interventions in human\u2013computer interaction. Interact Comput 295\u2013309","DOI":"10.1016\/j.intcom.2003.12.001"},{"key":"2683_CR3","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1080\/08839510590910174","volume":"19","author":"H Prendinger","year":"2005","unstructured":"Prendinger H, Ishizuka M (2005) The empathic companion: A character-based interface that addresses users\u2019 affective states. Appl Artif Intell 19:267\u2013285","journal-title":"Appl Artif Intell"},{"key":"2683_CR4","unstructured":"Serban IV, Alessandro S, Yoshua B, Aaron C, Joelle P (2015) building End-To-End dialogue systems using generative hierarchical neural network models. In: Proceedings of the Thirtieth AAAI conference on artificial intelligence, pp 3776\u20133783"},{"key":"2683_CR5","unstructured":"Iulian S, Alessandro S, Ryan L, Laurent C, Joelle P, Aaron C, Bengio Y (2017) A hierarchical latent variable Encoder-Decoder model for generating dialogues. In: Proceedings of the Thirty-First AAAI conference on artificial intelligence, pp 3295\u20133301"},{"key":"2683_CR6","unstructured":"Kaisheng Y, Geoffrey Z, Baolin P (2015) Attention with Intention for a Neural Network Conversation Model, arXiv:1510.08565"},{"key":"2683_CR7","unstructured":"Yookoon P, Jaemin C, Gunhee K (2018) A hierarchical latent structure for variational conversation modeling. In: Proceedings of the 2018 conference of the north american chapter of the association for computational linguistics: human language technologies, pp 1792\u20131801"},{"key":"2683_CR8","unstructured":"Lei S, Yang F, Haolan Z (2019) Modeling semantic relationship in multi-turn conversations with hierarchical latent variables. In: Proceedings of the 57th annual meeting of the association for computational linguistics"},{"key":"2683_CR9","doi-asserted-by":"publisher","unstructured":"Adoma AF, Henry N-M, Wenyu C (2021) Transformer models for text-based emotion detection: A review of BERT-based approaches. Artificial Intelligence Review. https:\/\/doi.org\/10.1007\/s10462-021-09958-2","DOI":"10.1007\/s10462-021-09958-2"},{"key":"2683_CR10","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1007\/s10489-015-0700-z","volume":"44","author":"K Yau-Hwang","year":"2016","unstructured":"Yau-Hwang K, Meng-hsuan F, Wen-Hao T, Kuan-Rong L, Ling-Yu C (2016) Integrated microblog sentiment analysis from users\u2019 social interaction patterns and textual opinions. Appl Intell 44:399\u2013413. https:\/\/doi.org\/10.1007\/s10489-015-0700-z","journal-title":"Appl Intell"},{"issue":"2","key":"2683_CR11","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1162\/COLI_a_00049","volume":"37","author":"M Taboada","year":"2011","unstructured":"Taboada M, Brooke J, Tofiloski M, Voll K, Stede M (2011) Lexicon-based methods for sentiment analysis. Comput Linguist 37(2):267\u2013307. https:\/\/doi.org\/10.1162\/COLI_a_00049","journal-title":"Comput Linguist"},{"issue":"5","key":"2683_CR12","doi-asserted-by":"publisher","first-page":"6000","DOI":"10.1016\/j.eswa.2011.11.107","volume":"39","author":"H Kang","year":"2012","unstructured":"Kang H, Yoo SJ, Han D (2012) Senti-lexicon and improved Nave Bayes algorithms for sentiment analysis of restaurant reviews. Expert Syst Appl 39(5):6000\u20136010","journal-title":"Expert Syst Appl"},{"key":"2683_CR13","doi-asserted-by":"publisher","first-page":"7149","DOI":"10.1007\/s10586-017-1077-z","volume":"22","author":"S Riaz","year":"2019","unstructured":"Riaz S, Fatima M, Kamran M et al (2019) Opinion mining on large scale data using sentiment analysis and k-means clustering. Clust Comput 22:7149\u20137164. https:\/\/doi.org\/10.1007\/s10586-017-1077-z","journal-title":"Clust Comput"},{"issue":"7","key":"2683_CR14","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.1002\/int.22105","volume":"34","author":"F Di Martino","year":"2019","unstructured":"Di Martino F et al (2019) A lightweight clustering-based approach to discover different emotional shades from social message streams. Int J Intell Syst 34(7):1505\u20131523. https:\/\/doi.org\/10.1002\/int.22105","journal-title":"Int J Intell Syst"},{"key":"2683_CR15","unstructured":"Hao Z, Minlie H, Tianyang Z, Xiaoyan Z, Bing L (2017) Emotional chatting machine: Emotional conversation generation with internal and external memory. In: Thirty-Second AAAI conference on artificial intelligence"},{"key":"2683_CR16","unstructured":"Sayan G, Mathieu C, Eugene L, Louis-Philippe M, Stefan S (2017) Affect-LM: A neural language model for customizable affective text generation. In: Proceedings of the 55th annual meeting of the association for computational linguistics, vol 1, pp 634\u2013642"},{"key":"2683_CR17","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-319-76941-7_12","volume-title":"Affective neural response generation, advances in information retrieval","author":"N Asghar","year":"2018","unstructured":"Asghar N, Poupart P, Hoey J, Jiang X, Mou L (2018) Affective neural response generation, advances in information retrieval. Springer International Publishing, Cham Switzerland, pp 154\u2013166"},{"key":"2683_CR18","unstructured":"Lei S, Yang F (2020) CDL: Curriculum dual learning for Emotion-Controllable response generation. In: Proceedings of the 58th annual meeting of the association for computational linguistics, pp 556\u2013566"},{"key":"2683_CR19","unstructured":"Kyunghyun C, Bart vM, Caglar G, Fethi B, Holger S, Bengio Y (2014) Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Proceedings of the 2014 conference on empirical methods in natural language processing, pp 1724\u20131734"},{"key":"2683_CR20","unstructured":"Li Y, Su UI, Shen X, Li W, Cao Z, Niu S (2017) DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset. In: Proceedings of the eighth international joint conference on natural language processing IJCNLP, vol 2017, pp 986\u2013995"},{"key":"2683_CR21","doi-asserted-by":"crossref","unstructured":"Poria S, Hazarika D, Majumder N, Cambria GNE, Mihalcea R (2019) MELD: A multimodal multi-party dataset for emotion recognition in conversations. In: Proceedings of the 57th conference of the association for computational linguistics ACL, vol 2019, pp 527\u2013536","DOI":"10.18653\/v1\/P19-1050"},{"key":"2683_CR22","unstructured":"Diederik K, Jimmy B (2015) Adam: A method for stochastic optimization. In: The 3rd international conference on learning representations, p 13"},{"key":"2683_CR23","doi-asserted-by":"crossref","unstructured":"Bowman Samuel R, Luke V, Oriol V, Andrew D, Rafal J, Samy B (2016) Generating sentences from a continuous space. In: Proceedings of The 20th SIGNLL conference on computational natural language learning, pp 10\u201321","DOI":"10.18653\/v1\/K16-1002"},{"key":"2683_CR24","unstructured":"Xi C, Diederik K, Tim S, Yan D, Prafulla D, John S, Ilya S, Pieter A (2017) Variational Lossy Autoencoder. In: The 5th international conference on learning representations"},{"key":"2683_CR25","unstructured":"Kishore P, Salim R, Todd W, Wei-Jing Z (2002) BLEU: A method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting on association for computational linguistics, pp 311\u2013318"},{"key":"2683_CR26","unstructured":"Forgues G, Pineau J, Larchev\u00eaque J-M, Tremblay \u0154 (2004) Bootstrapping dialog systems with word embeddings. In: Proceedings of the 42nd Annual Conference of the Association for Computational Linguistics, pp 605\u2013612"},{"key":"2683_CR27","unstructured":"Jiwei L, Michel G, Chris B, Jianfeng G, Bill D (2016) A Diversity-Promoting objective function for neural conversation models. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies, pp 110\u2013119"},{"key":"2683_CR28","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. In: Proceedings of the 31st international conference on neural information processing systems (NIPS\u201917), pp 6000\u20136010"},{"key":"2683_CR29","unstructured":"Liangchen L, Jingjing X, Junyang L, Qi Zeng , Xu S (2018) An Auto-Encoder matching model for learning Utterance-Level semantic dependency in dialogue generation. In: Proceedings of the 2018 conference on empirical methods in natural language processing, pp 702\u2013707"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-02683-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-021-02683-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-02683-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T07:02:38Z","timestamp":1645513358000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-021-02683-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,26]]},"references-count":29,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["2683"],"URL":"https:\/\/doi.org\/10.1007\/s10489-021-02683-x","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2021,7,26]]},"assertion":[{"value":"12 July 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 July 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}