{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T11:28:27Z","timestamp":1762342107507},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"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":["World Wide Web"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1007\/s11280-023-01185-9","type":"journal-article","created":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T13:01:37Z","timestamp":1689598897000},"page":"3303-3320","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Aspect sentiment quadruple extraction based on the sentence-guided grid tagging scheme"],"prefix":"10.1007","volume":"26","author":[{"given":"Linan","family":"Zhu","sequence":"first","affiliation":[]},{"given":"Yinwei","family":"Bao","sequence":"additional","affiliation":[]},{"given":"Minhao","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Jianxin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhechao","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Xiangjie","family":"Kong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,17]]},"reference":[{"key":"1185_CR1","doi-asserted-by":"publisher","unstructured":"Zhu, L., Xu, M., Xu, Y., Zhu, Z., Zhao, Y., Kong, X.: A multi-attribute decision making approach based on information extraction for real estate buyer profiling. World Wide Web, 1\u201319 (2022). https:\/\/doi.org\/10.1007\/s11280-022-01010-9","DOI":"10.1007\/s11280-022-01010-9"},{"issue":"6","key":"1185_CR2","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1177\/0165551510388123","volume":"36","author":"TT Thet","year":"2010","unstructured":"Thet, T.T., Na, J.-C., Khoo, C.S.: Aspect-based sentiment analysis of movie reviews on discussion boards. J. Inf. Sci. 36(6), 82\u2013848 (2010). https:\/\/doi.org\/10.1177\/0165551510388123","journal-title":"J. Inf. Sci."},{"key":"1185_CR3","doi-asserted-by":"publisher","unstructured":"Xie, S., Cao, J., Wu, Z., Liu, K., Tao, X., Xie, H.: Sentiment analysis of chinese e-commerce reviews based on bert. In: 2020 IEEE 18th International Conference on Industrial Informatics (INDIN), vol. 1, pp. 71\u2013718 (2020). https:\/\/doi.org\/10.1109\/INDIN45582.2020.9442190. IEEE","DOI":"10.1109\/INDIN45582.2020.9442190"},{"key":"1185_CR4","doi-asserted-by":"publisher","unstructured":"Yadav, V., Verma, P., Katiyar, V.: E-commerce product reviews using aspect based hindi sentiment analysis. In: 2021 International Conference on Computer Communication and Informatics (ICCCI), pp. 1\u20138 (2021). https:\/\/doi.org\/10.1109\/ICCCI50826.2021.9402365. IEEE","DOI":"10.1109\/ICCCI50826.2021.9402365"},{"key":"1185_CR5","doi-asserted-by":"publisher","unstructured":"Chandra, J.K., Cambria, E., Nanetti, A.: One belt, one road, one sentiment? a hybrid approach to gauging public opinions on the new silk road initiative. In: 2020 International Conference on Data Mining Workshops (ICDMW), pp. 7\u201314 (2020). https:\/\/doi.org\/10.1109\/ICDMW51313.2020.00011. IEEE","DOI":"10.1109\/ICDMW51313.2020.00011"},{"key":"1185_CR6","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.inffus.2020.03.003","volume":"61","author":"K Shuang","year":"2020","unstructured":"Shuang, K., Yang, Q., Loo, J., Li, R., Gu, M.: Feature distillation network for aspect-based sentiment analysis. Inform. Fus. 61, 13\u201323 (2020). https:\/\/doi.org\/10.1016\/j.inffus.2020.03.003","journal-title":"Inform. Fus."},{"key":"1185_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107220","volume":"227","author":"A Zhao","year":"2021","unstructured":"Zhao, A., Yu, Y.: Knowledge-enabled bert for aspect-based sentiment analysis. Knowledge-Based Systems 227, 107220 (2021). https:\/\/doi.org\/10.1016\/j.knosys.2021.107220","journal-title":"Knowledge-Based Systems"},{"key":"1185_CR8","doi-asserted-by":"publisher","unstructured":"Ren, Z.-M., Zheng, Y., Du, W.-L., Pan, X.: A joint model for extracting latent aspects and their ratings from online employee reviews. Front. Phys. 311 (2022). https:\/\/doi.org\/10.3389\/fphy.2022.822351","DOI":"10.3389\/fphy.2022.822351"},{"key":"1185_CR9","doi-asserted-by":"crossref","unstructured":"Zhao, H., Huang, L., Zhang, R., Lu, Q., Xue, H.: SpanMlt: A spanbased multi-task learning framework for pair-wise aspect and opinion terms extraction. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3239\u20133248. Association for Computational Linguistics, Online (2020).https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.296","DOI":"10.18653\/v1\/2020.acl-main.296"},{"key":"1185_CR10","doi-asserted-by":"crossref","unstructured":"Chen, S., Liu, J., Wang, Y., Zhang, W., Chi, Z.: Synchronous doublechannel recurrent network for aspect-opinion pair extraction. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 6515\u20136524. Association for Computational Linguistics, Online (2020).https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.582","DOI":"10.18653\/v1\/2020.acl-main.582"},{"issue":"14","key":"1185_CR11","doi-asserted-by":"publisher","first-page":"12875","DOI":"10.1609\/aaai.v35i14.17523","volume":"35","author":"L Gao","year":"2021","unstructured":"Gao, L., Wang, Y., Liu, T., Wang, J., Zhang, L., Liao, J.: Question-driven span labeling model for aspec-opinion pair extraction. Proc. AAAI Conf. Artif. Intell. 35(14), 12875\u201312883 (2021). https:\/\/doi.org\/10.1609\/aaai.v35i14.17523","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"1185_CR12","doi-asserted-by":"publisher","unstructured":"Wu, S., Fei, H., Ren, Y., Ji, D., Li, J.: Learn from syntax: Improving pairwise aspect and opinion terms extractionwith rich syntactic knowledge. arXiv:2105.02520 (2021). https:\/\/doi.org\/10.48550\/arXiv2105.02520","DOI":"10.48550\/arXiv2105.02520"},{"key":"1185_CR13","doi-asserted-by":"crossref","unstructured":"Schmitt, M., Steinheber, S., Schreiber, K., Roth, B.: Joint aspect and polarity classification for aspect-based sentiment analysis with end-to-end neural networks. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 1109\u20131114. Association for Computational Linguistics, Brussels, Belgium (2018). https:\/\/doi.org\/10.18653\/v1\/D18-1139","DOI":"10.18653\/v1\/D18-1139"},{"key":"1185_CR14","doi-asserted-by":"crossref","unstructured":"Cai, H., Tu, Y., Zhou, X., Yu, J., Xia, R.: Aspect-category based sentiment analysis with hierarchical graph convolutional network. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 833\u2013843. International Committee on Computational Linguistics, Barcelona, Spain (Online) (2020).https:\/\/doi.org\/10.18653\/v1\/2020.coling-main.72","DOI":"10.18653\/v1\/2020.coling-main.72"},{"key":"1185_CR15","doi-asserted-by":"crossref","unstructured":"Liu, J., Teng, Z., Cui, L., Liu, H., Zhang, Y.: Solving aspect category sentiment analysis as a text generation task. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 4406\u20134416. Association for Computational Linguistics, Online and Punta Cana, Dominican Republic (2021).https:\/\/doi.org\/10.18653\/v1\/2021.emnlp-main.361","DOI":"10.18653\/v1\/2021.emnlp-main.361"},{"key":"1185_CR16","doi-asserted-by":"publisher","unstructured":"Peng, H., Xu, L., Bing, L., Huang, F., Lu, W., Si, L.: Knowing what, how and why: A near complete solution for aspect-based sentiment analysis. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 8600\u20138607 (2020). https:\/\/doi.org\/10.1609\/aaai.v34i05.6383","DOI":"10.1609\/aaai.v34i05.6383"},{"key":"1185_CR17","doi-asserted-by":"publisher","unstructured":"Chen, Z., Qian, T.: Relation-aware collaborative learning for unified aspect-based sentiment analysis. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 3685\u20133694. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.340","DOI":"10.18653\/v1\/2020.acl-main.340"},{"key":"1185_CR18","doi-asserted-by":"publisher","unstructured":"Zhang, C., Li, Q., Song, D., Wang, B.: A multi-task learning framework for opinion triplet extraction. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 819\u2013828. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.findings-emnlp.72","DOI":"10.18653\/v1\/2020.findings-emnlp.72"},{"key":"1185_CR19","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3129483","author":"H Fei","year":"2021","unstructured":"Fei, H., Ren, Y., Zhang, Y., Ji, D.: Nonautoregressive encoder-decoder neural framework for end-to-end aspect-based sentiment triplet extraction. IEEE Transactions on Neural Networks and Learning Systems (2021). https:\/\/doi.org\/10.1109\/TNNLS.2021.3129483","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"1185_CR20","doi-asserted-by":"publisher","unstructured":"Zhang, W., Li, X., Deng, Y., Bing, L., Lam, W.: Towards generative aspect-based sentiment analysis. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 504\u2013510. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-short.64","DOI":"10.18653\/v1\/2021.acl-short.64"},{"key":"1185_CR21","doi-asserted-by":"publisher","unstructured":"Chen, Z., Huang, H., Liu, B., Shi, X., Jin, H.: Semantic and syntactic enhanced aspect sentiment triplet extraction. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp. 1474\u20131483. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.findings-acl.128","DOI":"10.18653\/v1\/2021.findings-acl.128"},{"key":"1185_CR22","doi-asserted-by":"publisher","unstructured":"Jiang, Q., Chen, L., Xu, R., Ao, X., Yang, M.: A challenge dataset and effective models for aspect-based sentiment 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. 6280\u20136285. Association for Computational Linguistics, Hong Kong, China (2019). https:\/\/doi.org\/10.18653\/v1\/D19-1654","DOI":"10.18653\/v1\/D19-1654"},{"issue":"6","key":"1185_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3350487","volume":"13","author":"P Zhu","year":"2019","unstructured":"Zhu, P., Chen, Z., Zheng, H., Qian, T.: Aspect aware learning for aspect category sentiment analysis. ACM Trans. Knowl. Discov. Data (TKDD) 13(6), 1\u201321 (2019). https:\/\/doi.org\/10.1145\/3350487","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"key":"1185_CR24","doi-asserted-by":"publisher","unstructured":"Li, Y., Yin, C., Zhong, S.-h., Pan, X.: Multi-instance multi-label learning networks for aspect-category sentiment analysis. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 3550\u20133560. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.287","DOI":"10.18653\/v1\/2020.emnlp-main.287"},{"key":"1185_CR25","doi-asserted-by":"publisher","unstructured":"Li, Y., Yin, C., Zhong, S.-h.: Sentence constituent-aware aspect-category sentiment analysis with graph attention networks. In: CCF International Conference on Natural Language Processing and Chinese Computing, Springer pp. 815\u2013827 (2020). https:\/\/doi.org\/10.1007\/978-3-030-60450-9_64","DOI":"10.1007\/978-3-030-60450-9_64"},{"key":"1185_CR26","doi-asserted-by":"publisher","unstructured":"Cai, H., Xia, R., Yu, J.: Aspect-category-opinion-sentiment quadruple extraction with implicit aspects and opinions. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 340\u2013350. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.29","DOI":"10.18653\/v1\/2021.acl-long.29"},{"key":"1185_CR27","doi-asserted-by":"publisher","unstructured":"Zhang, W., Deng, Y., Li, X., Yuan, Y., Bing, L., Lam, W.: Aspect sentiment quad prediction as paraphrase generation. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 9209\u20139219. Association for Computational Linguistics, Online and Punta Cana, Dominican Republic (2021). https:\/\/doi.org\/10.18653\/v1\/2021.emnlp-main.726","DOI":"10.18653\/v1\/2021.emnlp-main.726"},{"key":"1185_CR28","doi-asserted-by":"publisher","unstructured":"Fei, H., Li, F., Li, C., Wu, S., Li, J., Ji, D.: Inheriting the wisdom of predecessors: A multiplex cascade framework for unified aspect-based sentiment analysis. In: Raedt, L.D. (ed.) Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pp. 4121\u20134128. International Joint Conferences on Artificial Intelligence Organization, (2022). https:\/\/doi.org\/10.24963\/ijcai.2022\/572. MainTrack","DOI":"10.24963\/ijcai.2022\/572"},{"key":"1185_CR29","doi-asserted-by":"publisher","unstructured":"Yan, H., Dai, J., Ji, T., Qiu, X., Zhang, Z.: A unified generative framework for aspect-based sentiment analysis. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 2416\u20132429. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.188","DOI":"10.18653\/v1\/2021.acl-long.188"},{"key":"1185_CR30","doi-asserted-by":"publisher","unstructured":"Cai, Z., Fan, Q., Feris, R.S., Vasconcelos, N.: A unified multi-scale deep convolutional neural network for fast object detection. In: European Conference on Computer Vision, pp. 354\u2013370 (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_22. Springer","DOI":"10.1007\/978-3-319-46493-0_22"},{"issue":"5\u20136","key":"1185_CR31","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1016\/j.neunet.2005.06.042","volume":"18","author":"A Graves","year":"2005","unstructured":"Graves, A., Schmidhuber, J.: Framewise phoneme classification with bidirectional lstm and other neural network architectures. Neural Networks 18(5\u20136), 602\u2013610 (2005). https:\/\/doi.org\/10.1016\/j.neunet.2005.06.042","journal-title":"Neural Networks"},{"key":"1185_CR32","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. Adv. Neural. Inform. Proc. Syst. 30 (2017). https:\/\/doi.org\/10.48550\/arXiv.1706.03762"},{"key":"1185_CR33","doi-asserted-by":"publisher","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20139 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298594","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"1185_CR34","doi-asserted-by":"crossref","unstructured":"Wu, Z., Ying, C., Zhao, F., Fan, Z., Dai, X., Xia, R.: Grid tagging scheme for aspect-oriented fine-grained opinion extraction. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 2576\u20132585. Association for Computational Linguistics, Online (2020).https:\/\/doi.org\/10.18653\/v1\/2020.findings-emnlp.234","DOI":"10.18653\/v1\/2020.findings-emnlp.234"},{"key":"1185_CR35","doi-asserted-by":"publisher","unstructured":"Turney, P.: Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 417\u2013424. Association for Computational Linguistics, Philadelphia, Pennsylvania, USA (2002). https:\/\/doi.org\/10.3115\/1073083.1073153","DOI":"10.3115\/1073083.1073153"},{"key":"1185_CR36","doi-asserted-by":"publisher","unstructured":"Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? sentiment classification using machine learning techniques. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP 2002), pp. 79\u201386. Association for Computational Linguistics, (2002). https:\/\/doi.org\/10.3115\/1118693.1118704","DOI":"10.3115\/1118693.1118704"},{"key":"1185_CR37","doi-asserted-by":"crossref","unstructured":"Yu, H., Hatzivassiloglou, V.: Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In: Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, pp. 129\u2013136 (2003).https:\/\/aclanthology.org\/W03-1017","DOI":"10.3115\/1119355.1119372"},{"key":"1185_CR38","doi-asserted-by":"publisher","unstructured":"Li, B., Fei, H., Wu, Y., Zhang, J., Wu, S., Li, J., Liu, Y., Liao, L., Chua, T.-S., Li, F., et al.: Diaasq: A benchmark of conversational aspect-based sentiment quadruple analysis. arXiv:2211.05705 (2022). https:\/\/doi.org\/10.48550\/arXiv.2211.05705","DOI":"10.48550\/arXiv.2211.05705"},{"key":"1185_CR39","doi-asserted-by":"publisher","unstructured":"Areed, S., Alqaryouti, O., Siyam, B., Shaalan, K.: Aspect-based sentiment analysis for arabic government reviews. In: Recent Advances in NLP: the Case of Arabic Language, pp. 143\u2013162. Springer, (2020). https:\/\/doi.org\/10.1007\/978-3-030-34614-0_8","DOI":"10.1007\/978-3-030-34614-0_8"},{"issue":"1","key":"1185_CR40","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s10844-020-00622-9","volume":"57","author":"SS Eldin","year":"2021","unstructured":"Eldin, S.S., Mohammed, A., Eldin, A.S., Hefny, H.: An enhanced opinion retrieval approach via implicit feature identification. Journal of Intelligent Information Systems 57(1), 101\u2013126 (2021). https:\/\/doi.org\/10.1007\/s10844-020-00622-9","journal-title":"Journal of Intelligent Information Systems"},{"issue":"1","key":"1185_CR41","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1504\/IJDMMM.2016.075966","volume":"8","author":"F Lazhar","year":"2016","unstructured":"Lazhar, F., Yamina, T.-G.: Mining explicit and implicit opinions from reviews. Int. J Data Mining Modell. Manag. 8(1), 77\u201392 (2016). https:\/\/doi.org\/10.1504\/IJDMMM.2016.075966","journal-title":"Int. J Data Mining Modell. Manag."},{"key":"1185_CR42","doi-asserted-by":"publisher","unstructured":"Luo, H., Ji, L., Li, T., Jiang, D., Duan, N.: GRACE: Gradient harmonized and cascaded labeling for aspect-based sentiment analysis. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 54\u201364. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.findings-emnlp.6","DOI":"10.18653\/v1\/2020.findings-emnlp.6"},{"key":"1185_CR43","doi-asserted-by":"publisher","unstructured":"Liang, Y., Meng, F., Zhang, J., Chen, Y., Xu, J., Zhou, J.: An iterative multi-knowledge transfer network for aspect-based sentiment analysis. In: Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 1768\u20131780. Association for Computational Linguistics, Punta Cana, Dominican Republic (2021). https:\/\/doi.org\/10.18653\/v1\/2021.findings-emnlp.152","DOI":"10.18653\/v1\/2021.findings-emnlp.152"},{"key":"1185_CR44","doi-asserted-by":"publisher","unstructured":"Chen, P., Chen, S., Liu, J.: Hierarchical sequence labeling model for aspect sentiment triplet extraction. In: CCF International Conference on Natural Language Processing and Chinese Computing, pp. 654\u2013666 (2020) Springer. https:\/\/doi.org\/10.1007\/978-3-030-60450-9_52","DOI":"10.1007\/978-3-030-60450-9_52"},{"key":"1185_CR45","doi-asserted-by":"publisher","unstructured":"Xu, L., Li, H., Lu, W., Bing, L.: Position-aware tagging for aspect sentiment triplet extraction. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 2339\u20132349. Association for Computational Linguistics, Online (2020). https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.183","DOI":"10.18653\/v1\/2020.emnlp-main.183"},{"key":"1185_CR46","doi-asserted-by":"publisher","unstructured":"Zamil, A.A.A., Hasan, S., Baki, S.M.J., Adam, J.M., Zaman, I.: Emotion detection from speech signals using voting mechanism on classified frames. In: 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), pp. 281\u2013285 (2019). https:\/\/doi.org\/10.1109\/ICREST.2019.8644168. IEEE","DOI":"10.1109\/ICREST.2019.8644168"},{"key":"1185_CR47","doi-asserted-by":"publisher","unstructured":"Pennington, J., Socher, R., Manning, C.: GloVe: Global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543. Association for Computational Linguistics, Doha, Qatar (2014). https:\/\/doi.org\/10.3115\/v1\/D14-1162","DOI":"10.3115\/v1\/D14-1162"},{"key":"1185_CR48","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. (2014) arXiv:1412.6980"},{"issue":"1","key":"1185_CR49","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1162\/coli_a_00034","volume":"37","author":"G Qiu","year":"2011","unstructured":"Qiu, G., Liu, B., Bu, J., Chen, C.: Opinion word expansion and target extraction through double propagation. Comput. Linguistics 37(1), 9\u201327 (2011). https:\/\/doi.org\/10.1162\/coli_a_00034","journal-title":"Comput. Linguistics"},{"key":"1185_CR50","doi-asserted-by":"publisher","unstructured":"Wan, H., Yang, Y., Du, J., Liu, Y., Qi, K., Pan, J.Z.: Target-aspectsentiment joint detection for aspect-based sentiment analysis. In: Proc AAAI Conf. Artif. Intell, vol. 34, 9122\u20139129 (2020). https:\/\/doi.org\/10.1609\/aaai.v34i05.6447","DOI":"10.1609\/aaai.v34i05.6447"},{"key":"1185_CR51","doi-asserted-by":"publisher","unstructured":"Wang, W., Pan, S.J., Dahlmeier, D., Xiao, X.: Coupled multi-layer attentions for co-extraction of aspect and opinion terms. In: Proc AAAI Conf Artif Intell, vol. 31 (2017). https:\/\/doi.org\/10.1609\/aaai.v31i1.10974","DOI":"10.1609\/aaai.v31i1.10974"}],"container-title":["World Wide Web"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11280-023-01185-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11280-023-01185-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11280-023-01185-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T04:25:08Z","timestamp":1696998308000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11280-023-01185-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,17]]},"references-count":51,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,9]]}},"alternative-id":["1185"],"URL":"https:\/\/doi.org\/10.1007\/s11280-023-01185-9","relation":{},"ISSN":["1386-145X","1573-1413"],"issn-type":[{"value":"1386-145X","type":"print"},{"value":"1573-1413","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,17]]},"assertion":[{"value":"27 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 February 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2023","order":4,"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 competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}]}}