{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T13:40:44Z","timestamp":1762522844686,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031446986"},{"type":"electronic","value":"9783031446993"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-44699-3_17","type":"book-chapter","created":{"date-parts":[[2023,10,7]],"date-time":"2023-10-07T08:02:39Z","timestamp":1696665759000},"page":"185-196","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Enhancing Conversational Aspect-Based Sentiment Quadruple Analysis with\u00a0Context Fusion Encoding Method"],"prefix":"10.1007","author":[{"given":"Xisheng","family":"Xiao","sequence":"first","affiliation":[]},{"given":"Jiawei","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Qianer","family":"Li","sequence":"additional","affiliation":[]},{"given":"Peijie","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Yuhong","family":"Xu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,8]]},"reference":[{"key":"17_CR1","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.inffus.2022.10.004","volume":"91","author":"HT Phan","year":"2023","unstructured":"Phan, H.T., Nguyen, N.T., Hwang, D.: Aspect-level sentiment analysis: a survey of graph convolutional network methods. Inform. Fusion 91, 149\u2013172 (2023)","journal-title":"Inform. Fusion"},{"key":"17_CR2","unstructured":"Zhang, W., Li, X., Deng, Y., Bing, L., Lam, W.: A survey on aspect-based sentiment analysis: tasks, methods, and challenges. CoRR (2022)"},{"issue":"1","key":"17_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-02145-9","volume":"5","author":"B Liu","year":"2012","unstructured":"Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5(1), 1\u2013167 (2012)","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Li, R., Chen, H., Feng, F., Ma, Z., Wang, X., Hovy, E.: Dual graph convolutional networks for aspect-based sentiment analysis. In: ACL-IJCNLP (2021)","DOI":"10.18653\/v1\/2021.acl-long.494"},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Zhou, Z., Wang, Y.: Ssegcn: syntactic and semantic enhanced graph convolutional network for aspect-based sentiment analysis. In: NAACL-HLT (2022)","DOI":"10.18653\/v1\/2022.naacl-main.362"},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Liao, L., Gao, Y., Jie, Z., Lu, W.: To be closer: learning to link up aspects with opinions. In: EMNLP (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.317"},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Chen, S., Liu, J., Wang, Y., Zhang, W., Chi, Z.: Synchronous double-channel recurrent network for aspect-opinion pair extraction. In: ACL (2020)","DOI":"10.18653\/v1\/2020.acl-main.582"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Wu, Z., Ying, C., Zhao, F., Fan, Z., Dai, X., Xia, R.: Grid tagging scheme for end-to-end fine-grained opinion extraction. In: EMNLP (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.234"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Xu, L., Li, H., Lu, W., Bing, L.: Position-aware tagging for aspect sentiment triplet extraction. In: EMNLP (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.183"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Cai, H., Xia, R., Yu, J.: Aspect-category-opinion-sentiment quadruple extraction with implicit aspects and opinions. In: ACL-IJCNLP (2021)","DOI":"10.18653\/v1\/2021.acl-long.29"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Zhang, W., Deng, Y., Li, X., Yuan, Y., Bing, L., Lam, W.: Aspect sentiment quad prediction as paraphrase generation. In: EMNLP (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.726"},{"key":"17_CR12","doi-asserted-by":"crossref","unstructured":"Li, B., et al.: Diaasq: A benchmark of conversational aspect-based sentiment quadruple analysis. In: Findings of ACL (2023)","DOI":"10.18653\/v1\/2023.findings-acl.849"},{"key":"17_CR13","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s10772-011-9125-1","volume":"15","author":"SG Koolagudi","year":"2012","unstructured":"Koolagudi, S.G., Rao, K.S.: Emotion recognition from speech: a review. Inter. J. Speech Technol. 15, 99\u2013117 (2012)","journal-title":"Inter. J. Speech Technol."},{"key":"17_CR14","unstructured":"Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Pre-training of deep bidirectional transformers for language understanding. In: NAACL-HLT, Bert (2019)"},{"key":"17_CR15","unstructured":"Vaswani, A., et al.: Attention is all you need. In: NIPS (2017)"},{"key":"17_CR16","unstructured":"Liang, X., et al.: R-drop: regularized dropout for neural networks. In: NeurIPS (2021)"},{"key":"17_CR17","unstructured":"Miyato, T., Dai, A.M., Goodfellow, I.: Adversarial training methods for semi-supervised text classification. In: ICLR (2017)"},{"key":"17_CR18","doi-asserted-by":"crossref","unstructured":"Bao, X., Wang, Z., Jiang, X., Xiao, R., Li, S.: Aspect-based sentiment analysis with opinion tree generation. In: IJCAI (2022)","DOI":"10.24963\/ijcai.2022\/561"},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Mao, Y., Shen, Y., Yang, J., Zhu, X., Cai, L.: Seq2path: generating sentiment tuples as paths of a tree. In: Findings of ACL (2022)","DOI":"10.18653\/v1\/2022.findings-acl.174"},{"key":"17_CR20","doi-asserted-by":"crossref","unstructured":"Lu, Y.: Unified structure generation for universal information extraction. In: ACL (2022)","DOI":"10.18653\/v1\/2022.acl-long.395"},{"key":"17_CR21","unstructured":"Jianlin, S., Yu, L., Pan, S., Murtadha, A., Wen, B., Liu, Y.: Roformer: enhanced transformer with rotary position embedding. CoRR (2021)"},{"key":"17_CR22","doi-asserted-by":"crossref","unstructured":"Barnes, J., Kurtz, R., Oepen, S., \u00d8vrelid, L., Velldal, E.: Structured sentiment analysis as dependency graph parsing. In: ACL\/IJCNLP (2021)","DOI":"10.18653\/v1\/2021.acl-long.263"},{"key":"17_CR23","doi-asserted-by":"publisher","first-page":"3504","DOI":"10.1109\/TASLP.2021.3124365","volume":"29","author":"Y Cui","year":"2021","unstructured":"Cui, Y., Che, W., Liu, T., Qin, B., Yang, Z.: Pre-training with whole word masking for Chinese bert. IEEE\/ACM Trans. Audio Speech Lang. Process. 29, 3504\u20133514 (2021)","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"17_CR24","unstructured":"Liu, Y., et al.: Roberta: a robustly optimized bert pretraining approach. CoRR (2019)"},{"key":"17_CR25","unstructured":"Eberts, M., Ulges, A.: Span-based joint entity and relation extraction with transformer pre-training. In: ECAI (2020)"},{"key":"17_CR26","unstructured":"Lu, X., Chia, Y.K., Bing, L.: Learning span-level interactions for aspect sentiment triplet extraction In: ACL\/IJCNLP (2021)"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-44699-3_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T06:06:43Z","timestamp":1698473203000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44699-3_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031446986","9783031446993"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44699-3_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"8 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Foshan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2023\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Softconf","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"478","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"143","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}