{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:53:12Z","timestamp":1763196792342,"version":"3.45.0"},"publisher-location":"Singapore","reference-count":32,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819533480","type":"print"},{"value":"9789819533497","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-3349-7_26","type":"book-chapter","created":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:50:11Z","timestamp":1763196611000},"page":"336-350","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dialogue Multi-dimensional Feature Dividing and\u00a0Fusion Model for\u00a0Dialogue Aspect-Based Sentiment Quadruple Analysis"],"prefix":"10.1007","author":[{"given":"Ying","family":"Ding","sequence":"first","affiliation":[]},{"given":"Yanxu","family":"Mao","sequence":"additional","affiliation":[]},{"given":"Shunli","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,16]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Wang, D., Li, T., Zhu, S., Ding, C.: Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization. In: Proceedings of the 31st Annual International ACM SIGIR, pp. 307\u2013314 (2008)","DOI":"10.1145\/1390334.1390387"},{"issue":"23","key":"26_CR2","doi-asserted-by":"publisher","first-page":"11091","DOI":"10.3390\/app112311091","volume":"11","author":"A Farkhod","year":"2021","unstructured":"Farkhod, A., Abdusalomov, A., et al.: LDA-based topic modeling sentiment analysis using topic\/document\/sentence (TDS) model. Appl. Sci. 11(23), 11091 (2021)","journal-title":"Appl. Sci."},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Fan, S., Lin, C., et\u00a0al.: Sentiment-aware word and sentence level pre-training for sentiment analysis. In: Proceedings of EMNLP, pp. 4984\u20134994 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.332"},{"key":"26_CR4","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.neucom.2021.07.072","volume":"462","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Wang, J., et al.: Conciseness is better: recurrent attention LSTM model for document-level sentiment analysis. Neurocomputing 462, 101\u2013112 (2021)","journal-title":"Neurocomputing"},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Fei, H., Ren, Y., et al.: Latent target-opinion as prior for document-level sentiment classification: a variational approach from fine-grained perspective. In Proceedings of the Web Conference, pp. 553\u2013564 (2021)","DOI":"10.1145\/3442381.3449789"},{"key":"26_CR6","doi-asserted-by":"crossref","unstructured":"Cai, H., Ma, H., et\u00a0al.: A joint coreference-aware approach to document-level target sentiment analysis. In: Proceedings of ACL, pp. 12149\u201312160 (2024)","DOI":"10.18653\/v1\/2024.acl-long.657"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Xiao, L., Mao, R., et\u00a0al.: Vanessa: visual connotation and aesthetic attributes understanding network for multimodal aspect-based sentiment analysis. In: Findings of EMNLP, pp. 11486\u201311500 (2024)","DOI":"10.18653\/v1\/2024.findings-emnlp.671"},{"key":"26_CR8","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: Proceedings of ACL-IJCNLP, pp. 6319\u20136329 (2021)","DOI":"10.18653\/v1\/2021.acl-long.494"},{"issue":"11","key":"26_CR9","first-page":"11019","volume":"35","author":"W Zhang","year":"2022","unstructured":"Zhang, W., Li, X., et al.: A survey on aspect-based sentiment analysis: tasks, methods, and challenges. IEEE TKDE 35(11), 11019\u201311038 (2022)","journal-title":"IEEE TKDE"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Li, B., Fei, H., Li, F., et\u00a0al.: DiaASQ: a benchmark of conversational aspect-based sentiment quadruple analysis. In: Findings of ACL, pp. 13449\u201313467 (2023)","DOI":"10.18653\/v1\/2023.findings-acl.849"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Zhou, C., Zhijing, W., et al.: Span-pair interaction and tagging for dialogue-level aspect-based sentiment quadruple analysis. In: Proceedings of the ACM on Web Conference, pp. 3995\u20134005 (2024)","DOI":"10.1145\/3589334.3645355"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Huang, P., Xiao, X., Xu, Y., Chen, J.: DMIN: a discourse-specific multi-granularity integration network for conversational aspect-based sentiment quadruple analysis. In: Findings of ACL, pp. 16326\u201316338 (2024)","DOI":"10.18653\/v1\/2024.findings-acl.966"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Luo, X., Yang, M., Wang, Y.: Overcome noise and bias: segmentation-aided multi-granularity denoising and debiasing for enhanced quarduples extraction in dialogue. In: Proceedings of EMNLP, pp. 839\u2013856 (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.49"},{"key":"26_CR14","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhang, W., Li, B., et\u00a0al.: Dynamic multi-scale context aggregation for conversational aspect-based sentiment quadruple analysis. In: 2024-2024 IEEE International Conference on ICASSP, pp. 11241\u201311245. IEEE (2024)","DOI":"10.1109\/ICASSP48485.2024.10447873"},{"key":"26_CR16","doi-asserted-by":"crossref","unstructured":"Li, B., Li, Y., Jia, S., et\u00a0al.: Triple GNNS: introducing syntactic and semantic information for conversational aspect-based quadruple sentiment analysis. arXiv preprint arXiv:2403.10065 (2024)","DOI":"10.1109\/CSCWD61410.2024.10580730"},{"key":"26_CR17","unstructured":"Eberts, M., Ulges, A.: Span-based joint entity and relation extraction with transformer pre-training. In: ECAI 2020, pp. 2006\u20132013. IOS Press (2020)"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Cai, C., Zhao, Q., Xu, R., Qin, B.: Improving conversational aspect-based sentiment quadruple analysis with overall modeling. In: CCF International Conference on NLPCC, pp. 149\u2013161. Springer (2023)","DOI":"10.1007\/978-3-031-44699-3_14"},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Guo, Z., Zhang, Y., Lu, W.: Attention guided graph convolutional networks for relation extraction. In: Proceedings of ACL, pp. 241\u2013251 (2019)","DOI":"10.18653\/v1\/P19-1024"},{"key":"26_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, W., Deng, Y., et\u00a0al.: Aspect sentiment quad prediction as paraphrase generation. In: Proceedings of EMNLP, pp. 9209\u20139219 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.726"},{"key":"26_CR21","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., Mann, B., Ryder, N., et al.: Language models are few-shot learners. Adv. NeurIPS 33, 1877\u20131901 (2020)","journal-title":"Adv. NeurIPS"},{"key":"26_CR22","doi-asserted-by":"crossref","unstructured":"Xu, L., Chia, Y.K., et\u00a0al.: Learning span-level interactions for aspect sentiment triplet extraction. In: Proceedings of ACL-IJCNLP, pp. 4755\u20134766 (2021)","DOI":"10.18653\/v1\/2021.acl-long.367"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yang, Y., et\u00a0al.: Boundary-driven table-filling for aspect sentiment triplet extraction. In: Proceedings of EMNLP, pp. 6485\u20136498 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.435"},{"key":"26_CR24","doi-asserted-by":"publisher","first-page":"18462","DOI":"10.1609\/aaai.v38i16.29807","volume":"38","author":"B Li","year":"2024","unstructured":"Li, B., Fei, H., et al.: Harnessing holistic discourse features and triadic interaction for sentiment quadruple extraction in dialogues. Proc. AAAI 38, 18462\u201318470 (2024)","journal-title":"Proc. AAAI"},{"key":"26_CR25","doi-asserted-by":"crossref","unstructured":"Mao, Y., Cui, T., Ding, Y.: Enhancing logical rules based on self-distillation for document-level relation extraction. In: CCF International Conference on Natural Language Processing and Chinese Computing, pp. 406\u2013418. Springer (2024)","DOI":"10.1007\/978-981-97-9431-7_31"},{"issue":"9","key":"26_CR26","first-page":"3848","volume":"21","author":"L Zhao","year":"2019","unstructured":"Zhao, L., Song, Y., et al.: T-GCN: a temporal graph convolutional network for traffic prediction. IEEE TITS 21(9), 3848\u20133858 (2019)","journal-title":"IEEE TITS"},{"key":"26_CR27","unstructured":"Vaswani, A.: Attention is all you need. In: Advances in NeurIPS (2017)"},{"key":"26_CR28","doi-asserted-by":"publisher","first-page":"127063","DOI":"10.1016\/j.neucom.2023.127063","volume":"568","author":"S Jianlin","year":"2024","unstructured":"Jianlin, S., Ahmed, M., et al.: RoFormer: enhanced transformer with rotary position embedding. Neurocomputing 568, 127063 (2024)","journal-title":"Neurocomputing"},{"key":"26_CR29","doi-asserted-by":"crossref","unstructured":"Barnes, J., Kurtz, R., et\u00a0al.: Structured sentiment analysis as dependency graph parsing. In: Proceedings of ACL-IJCNLP, pp. 3387\u20133402 (2021)","DOI":"10.18653\/v1\/2021.acl-long.263"},{"key":"26_CR30","doi-asserted-by":"crossref","unstructured":"Cai, H., Xia, R., Yu, J.: Aspect-category-opinion-sentiment quadruple extraction with implicit aspects and opinions. In: Proceedings of ACL-IJCNLP, pp. 340\u2013350 (2021)","DOI":"10.18653\/v1\/2021.acl-long.29"},{"key":"26_CR31","unstructured":"Liu, Y., Ott, M., Goyal, N.: Roberta: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"26_CR32","first-page":"3504","volume":"29","author":"Y Cui","year":"2021","unstructured":"Cui, Y., Che, W., et al.: Pre-training with whole word masking for Chinese BERT. IEEE\/ACM TASLP 29, 3504\u20133514 (2021)","journal-title":"IEEE\/ACM TASLP"}],"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\/978-981-95-3349-7_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:50:16Z","timestamp":1763196616000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3349-7_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,16]]},"ISBN":["9789819533480","9789819533497"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3349-7_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,16]]},"assertion":[{"value":"16 November 2025","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":"Urumqi","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2025\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}