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Inf. Syst."],"published-print":{"date-parts":[[2021,10,31]]},"abstract":"<jats:p>\n            The consistency of a response to a given post at the\n            <jats:bold>\n              <jats:italic>semantic<\/jats:italic>\n            <\/jats:bold>\n            level and\n            <jats:bold>\n              <jats:italic>emotional<\/jats:italic>\n            <\/jats:bold>\n            level is essential for a dialogue system to deliver humanlike interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem and proposes a\n            <jats:italic>unified<\/jats:italic>\n            end-to-end neural architecture, which is capable of simultaneously encoding the\n            <jats:italic>semantics<\/jats:italic>\n            and the\n            <jats:italic>emotions<\/jats:italic>\n            in a post and leveraging target information to generate more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed method outperforms the state-of-the-art methods in terms of both content coherence and emotion appropriateness.\n          <\/jats:p>","DOI":"10.1145\/3456414","type":"journal-article","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T13:57:35Z","timestamp":1629208655000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Target-guided Emotion-aware Chat Machine"],"prefix":"10.1145","volume":"39","author":[{"given":"Wei","family":"Wei","sequence":"first","affiliation":[{"name":"Cognitive Computing and Intelligent Information Processing (CCIIP) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayi","family":"Liu","sequence":"additional","affiliation":[{"name":"Cognitive Computing and Intelligent Information Processing (CCIIP) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianling","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guibing","family":"Guo","sequence":"additional","affiliation":[{"name":"Software College, Northeastern University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feida","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Information Systems, Singapore Management University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Hubei Engineering Research Center on Big Data Security, School of Cyber Science and Engineering, Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuchong","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Feng","sequence":"additional","affiliation":[{"name":"Inception Institute of Artificial Intelligence Abu Dhabi, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,8,17]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. 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