{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T20:07:42Z","timestamp":1774555662626,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,7,30]],"date-time":"2022-07-30T00:00:00Z","timestamp":1659139200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,30]],"date-time":"2022-07-30T00:00:00Z","timestamp":1659139200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62141201"],"award-info":[{"award-number":["62141201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["01IS21086"],"award-info":[{"award-number":["01IS21086"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Inf Syst"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s10844-022-00729-1","type":"journal-article","created":{"date-parts":[[2022,7,30]],"date-time":"2022-07-30T18:02:56Z","timestamp":1659204176000},"page":"97-117","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Exploring rich structure information for aspect-based sentiment classification"],"prefix":"10.1007","volume":"60","author":[{"given":"Ling","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8239-7176","authenticated-orcid":false,"given":"Xiaofei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiafeng","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Dietze","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,30]]},"reference":[{"key":"729_CR1","doi-asserted-by":"publisher","unstructured":"Bahdanau, D., Cho, K., Bengio, Y. (2015) Neural machine translation by jointly learning to align and translate. In Proceedings of the 3rd International Conference on Learning Representations, https:\/\/doi.org\/10.48550\/arXiv.1409.0473","DOI":"10.48550\/arXiv.1409.0473"},{"issue":"1","key":"729_CR2","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s10844-019-00591-8","volume":"55","author":"P Berka","year":"2020","unstructured":"Berka, P. (2020). Sentiment analysis using rule-based and case-based reasoning. Journal of Intelligent Information Systems, 55(1), 51\u201366. https:\/\/doi.org\/10.1007\/s10844-019-00591-8","journal-title":"Journal of Intelligent Information Systems"},{"key":"729_CR3","doi-asserted-by":"publisher","unstructured":"Chen, P., Sun, Z., Bing, L., Yang, W. (2017) Recurrent attention network on memory for aspect sentiment analysis. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (pp. 452\u2013461), https:\/\/doi.org\/10.18653\/v1\/d17-1047","DOI":"10.18653\/v1\/d17-1047"},{"key":"729_CR4","doi-asserted-by":"publisher","unstructured":"Conneau, A., Schwenk, H., Barrault, L., LeCun, Y. (2017) Very deep convolutional networks for text classification. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (pp. 1107\u20131116), https:\/\/doi.org\/10.18653\/v1\/e17-1104","DOI":"10.18653\/v1\/e17-1104"},{"key":"729_CR5","doi-asserted-by":"publisher","unstructured":"Cui, Y., Chen, Z., Wei, S., Wang, S., Liu, T., Hu, G. (2017) Attention-over-attention neural networks for reading comprehension. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (pp. 593\u2013602), https:\/\/doi.org\/10.18653\/v1\/P17-1055","DOI":"10.18653\/v1\/P17-1055"},{"key":"729_CR6","doi-asserted-by":"publisher","unstructured":"Dong L, Wei F, Tan C, Tang D, Zhou M, Xu K (2014) Adaptive recursive neural network for target-dependent twitter sentiment classification. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (pp. 49\u201354), https:\/\/doi.org\/10.3115\/v1\/p14-2009","DOI":"10.3115\/v1\/p14-2009"},{"key":"729_CR7","unstructured":"Gu, S., Zhang, L., Hou, Y., Song, Y. (2018) A position-aware bidirectional attention network for aspect-level sentiment analysis. In Proceedings of the 27th International Conference on Computational Linguistics (pp. 774\u2013784), https:\/\/aclanthology.org\/C18-1066."},{"issue":"8","key":"729_CR8","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735\u20131780. https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Computation"},{"key":"729_CR9","doi-asserted-by":"publisher","unstructured":"Hou, X., Qi, P., Wang, G., Ying, R., Huang, J., He, X., Zhou, B. (2021) Graph ensemble learning over multiple dependency trees for aspect-level sentiment classification. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (pp. 2884\u20132894), https:\/\/doi.org\/10.18653\/v1\/2021.naacl-main.229","DOI":"10.18653\/v1\/2021.naacl-main.229"},{"key":"729_CR10","doi-asserted-by":"publisher","unstructured":"Huang, B., Ou, Y., Carley, K.M. (2018) Aspect level sentiment classification with attention-over-attention neural networks. In Proceedings of the 11th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation (pp 197\u2013206), https:\/\/doi.org\/10.1007\/978-3-319-93372-6_22","DOI":"10.1007\/978-3-319-93372-6_22"},{"key":"729_CR11","doi-asserted-by":"publisher","unstructured":"Huang, L., Ma, D., Li, S., Zhang, X., Wang, H. (2019) Text level graph neural network for text classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (pp 3442\u20133448), https:\/\/doi.org\/10.18653\/v1\/D19-1345","DOI":"10.18653\/v1\/D19-1345"},{"key":"729_CR12","doi-asserted-by":"publisher","unstructured":"Huang, L., Sun, X., Li, S., Zhang, L., Wang, H. (2020) Syntax-aware graph attention network for aspect-level sentiment classification. In Proceedings of the 28th International Conference on Computational Linguistics (pp 799\u2013810), https:\/\/doi.org\/10.18653\/v1\/2020.coling-main.69","DOI":"10.18653\/v1\/2020.coling-main.69"},{"key":"729_CR13","doi-asserted-by":"publisher","unstructured":"Kalchbrenner, N., Grefenstette, E., Blunsom, P. (2014) A convolutional neural network for modelling sentences. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (pp. 655\u2013665), https:\/\/doi.org\/10.3115\/v1\/p14-1062","DOI":"10.3115\/v1\/p14-1062"},{"key":"729_CR14","doi-asserted-by":"publisher","unstructured":"Kiritchenko, S., Zhu, X., Cherry, C., Mohammad, S. (2014) Nrc-canada-2014: Detecting aspects and sentiment in customer reviews. In Proceedings of the 8th International Workshop on Semantic Evaluation (pp. 437\u2013442), https:\/\/doi.org\/10.3115\/v1\/s14-2076","DOI":"10.3115\/v1\/s14-2076"},{"key":"729_CR15","doi-asserted-by":"publisher","unstructured":"Li, X., Bing, L., Lam, W., Shi, B. (2018) Transformation networks for target-oriented sentiment classification. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (pp. 946\u2013956), https:\/\/doi.org\/10.18653\/v1\/P18-1087","DOI":"10.18653\/v1\/P18-1087"},{"key":"729_CR16","doi-asserted-by":"publisher","unstructured":"Liang, B., Du, J., Xu, R., Li, B., Huang, H. (2019) Context-aware embedding for targeted aspect-based sentiment analysis. In Proceedings of the 57th Conference of the Association for Computational Linguistics (pp 4678\u20134683), https:\/\/doi.org\/10.18653\/v1\/p19-1462","DOI":"10.18653\/v1\/p19-1462"},{"key":"729_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107643","volume":"235","author":"B Liang","year":"2022","unstructured":"Liang, B., Su, H., Gui, L., Cambria, E., & Xu, R. (2022). Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks. Knowledge-Based Systems, 235, 107643. https:\/\/doi.org\/10.1016\/j.knosys.2021.107643","journal-title":"Knowledge-Based Systems"},{"key":"729_CR18","doi-asserted-by":"publisher","unstructured":"Linmei, H., Yang, T., Shi, C., Ji, H., Li, X. (2019) Heterogeneous graph attention networks for semi-supervised short text classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (pp 4823\u20134832), https:\/\/doi.org\/10.18653\/v1\/D19-1488","DOI":"10.18653\/v1\/D19-1488"},{"key":"729_CR19","doi-asserted-by":"publisher","unstructured":"Liu, J., Zhang, Y. (2017) Attention modeling for targeted sentiment. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (pp. 572\u2013577), https:\/\/doi.org\/10.18653\/v1\/e17-2091","DOI":"10.18653\/v1\/e17-2091"},{"key":"729_CR20","doi-asserted-by":"publisher","unstructured":"Ma, D., Li, S., Zhang, X., Wang, H. (2017) Interactive attention networks for aspect-level sentiment classification. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (pp. 4068\u20134074), https:\/\/doi.org\/10.24963\/ijcai.2017\/568","DOI":"10.24963\/ijcai.2017\/568"},{"issue":"12","key":"729_CR21","doi-asserted-by":"publisher","first-page":"2127","DOI":"10.1109\/TASLP.2019.2942160","volume":"27","author":"Q Ma","year":"2019","unstructured":"Ma, Q., Yu, L., Tian, S., Chen, E., & Ng, W. W. Y. (2019). Global-local mutual attention model for text classification. IEEE ACM Trans Audio Speech Lang Process, 27(12), 2127\u20132139. https:\/\/doi.org\/10.1109\/TASLP.2019.2942160","journal-title":"IEEE ACM Trans Audio Speech Lang Process"},{"key":"729_CR22","doi-asserted-by":"publisher","unstructured":"Pennington, J., Socher, R., Manning, C.D. (2014) Glove: Global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (pp. 1532\u20131543), https:\/\/doi.org\/10.3115\/v1\/d14-1162","DOI":"10.3115\/v1\/d14-1162"},{"key":"729_CR23","doi-asserted-by":"publisher","unstructured":"Pontiki, M., Galanis, D., Pavlopoulos, J., et\u00a0al. (2014) Semeval-2014 task 4: Aspect based sentiment analysis. In Proceedings of the 8th International Workshop on Semantic Evaluation (pp. 27\u201335), https:\/\/doi.org\/10.3115\/v1\/s14-2004","DOI":"10.3115\/v1\/s14-2004"},{"key":"729_CR24","doi-asserted-by":"publisher","unstructured":"Pontiki, M., Galanis, D., Papageorgiou, H., Manandhar, S., Androutsopoulos, I. (2015) Semeval-2015 task 12: Aspect based sentiment analysis. In Proceedings of the 9th International Workshop on Semantic Evaluation (pp. 486\u2013495), https:\/\/doi.org\/10.18653\/v1\/s15-2082","DOI":"10.18653\/v1\/s15-2082"},{"key":"729_CR25","doi-asserted-by":"publisher","unstructured":"Pontiki, M., Galanis, D., Papageorgiou, H., Androutsopoulos, I., Manandhar, S., Al-Smadi, M., Al-Ayyoub, M., Zhao, Y., Qin, B., De\u00a0Clercq, O., et\u00a0al. (2016) Semeval-2016 task 5: Aspect based sentiment analysis. In Proceedings of the 10th International Workshop on Semantic Evaluation (pp. 19\u201330), https:\/\/doi.org\/10.18653\/v1\/s16-1055","DOI":"10.18653\/v1\/s16-1055"},{"issue":"2","key":"729_CR26","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1007\/s10844-020-00616-7","volume":"56","author":"LG Singh","year":"2021","unstructured":"Singh, L. G., & Singh, S. R. (2021). Empirical study of sentiment analysis tools and techniques on societal topics. Journal of Intelligent Information Systems, 56(2), 379\u2013407. https:\/\/doi.org\/10.1007\/s10844-020-00616-7","journal-title":"Journal of Intelligent Information Systems"},{"key":"729_CR27","doi-asserted-by":"publisher","unstructured":"Sun, K., Zhang, R., Mensah, S., Mao, Y., Liu, X. (2019) Aspect-level sentiment analysis via convolution over dependency tree. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (pp. 5678\u20135687), https:\/\/doi.org\/10.18653\/v1\/D19-1569","DOI":"10.18653\/v1\/D19-1569"},{"key":"729_CR28","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1512.01100","author":"D Tang","year":"2015","unstructured":"Tang, D., Qin, B., Feng, X., & Liu, T. (2015). Target-dependent sentiment classification with long short term memory.https:\/\/doi.org\/10.48550\/arXiv.1512.01100","journal-title":"Target-dependent sentiment classification with long short term memory."},{"key":"729_CR29","doi-asserted-by":"publisher","unstructured":"Tang, D., Qin, B., Feng, X., Liu, T. (2016a) Effective lstms for target-dependent sentiment classification. In Proceedings of the 25th International Conference on Computational Linguistics (pp. 3298\u20133307), https:\/\/doi.org\/10.48550\/arXiv.1512.01100","DOI":"10.48550\/arXiv.1512.01100"},{"key":"729_CR30","doi-asserted-by":"publisher","unstructured":"Tang, D., Qin, B., Liu, T. (2016b) Aspect level sentiment classification with deep memory network. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (pp. 214\u2013224), https:\/\/doi.org\/10.18653\/v1\/d16-1021","DOI":"10.18653\/v1\/d16-1021"},{"key":"729_CR31","doi-asserted-by":"publisher","unstructured":"Wagner, J., Arora, P., Cortes, S., Barman, U., Bogdanova, D., Foster, J., Tounsi, L. (2014) DCU: aspect-based polarity classification for semeval task 4. In Proceedings of the 8th International Workshop on Semantic Evaluation (pp. 223\u2013229), https:\/\/doi.org\/10.3115\/v1\/s14-2036","DOI":"10.3115\/v1\/s14-2036"},{"key":"729_CR32","doi-asserted-by":"publisher","unstructured":"Wang, G., Ying, R., Huang, J., Leskovec, J. (2021) Multi-hop attention graph neural networks. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (pp. 3089\u20133096), https:\/\/doi.org\/10.24963\/ijcai.2021\/425","DOI":"10.24963\/ijcai.2021\/425"},{"key":"729_CR33","doi-asserted-by":"publisher","unstructured":"Wang, Y., Huang, M., Zhu, X., Zhao, L. (2016) Attention-based lstm for aspect-level sentiment classification. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (pp. 606\u2013615), https:\/\/doi.org\/10.18653\/v1\/d16-1058","DOI":"10.18653\/v1\/d16-1058"},{"key":"729_CR34","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.neucom.2021.10.091","volume":"471","author":"L Xiao","year":"2022","unstructured":"Xiao, L., Xue, Y., Wang, H., Hu, X., Gu, D., & Zhu, Y. (2022). Exploring fine-grained syntactic information for aspect-based sentiment classification with dual graph neural networks. Neurocomputing, 471, 48\u201359. https:\/\/doi.org\/10.1016\/j.neucom.2021.10.091","journal-title":"Neurocomputing"},{"key":"729_CR35","doi-asserted-by":"publisher","unstructured":"Xue, W., Li, T. (2018) Aspect based sentiment analysis with gated convolutional networks. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (pp. 2514\u20132523), https:\/\/doi.org\/10.18653\/v1\/P18-1234","DOI":"10.18653\/v1\/P18-1234"},{"key":"729_CR36","doi-asserted-by":"crossref","unstructured":"Yang, M., Tu, W., Wang, J., Xu, F., Chen, X. (2017) Attention based LSTM for target dependent sentiment classification. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (pp. 5013\u20135014), https:\/\/dl.acm.org\/doi\/10.5555\/3297863.3297977.","DOI":"10.1609\/aaai.v31i1.11061"},{"key":"729_CR37","doi-asserted-by":"publisher","unstructured":"Yao, L., Mao, C., Luo, Y. (2019) Graph convolutional networks for text classification. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (pp. 7370\u20137377), https:\/\/doi.org\/10.1609\/aaai.v33i01.33017370","DOI":"10.1609\/aaai.v33i01.33017370"},{"key":"729_CR38","doi-asserted-by":"publisher","unstructured":"Zhang, C., Li, Q., Song, D. (2019) Aspect-based sentiment classification with aspect-specific graph convolutional networks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (pp. 4567\u20134577), https:\/\/doi.org\/10.18653\/v1\/D19-1464","DOI":"10.18653\/v1\/D19-1464"},{"key":"729_CR39","doi-asserted-by":"publisher","unstructured":"Zhang, M., Qian, T. (2020) Convolution over hierarchical syntactic and lexical graphs for aspect level sentiment analysis. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (pp. 3540\u20133549), https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.286","DOI":"10.18653\/v1\/2020.emnlp-main.286"},{"key":"729_CR40","doi-asserted-by":"publisher","unstructured":"Zhou, P., Qi, Z., Zheng, S., Xu, J., Bao, H., Xu, B. (2016) Text classification improved by integrating bidirectional LSTM with two-dimensional max pooling. In Proceedings of the 26th International Conference on Computational Linguistics (pp. 3485\u20133495), https:\/\/doi.org\/10.48550\/arXiv.1611.06639","DOI":"10.48550\/arXiv.1611.06639"},{"key":"729_CR41","doi-asserted-by":"publisher","first-page":"115712","DOI":"10.1016\/j.eswa.2021.115712","volume":"186","author":"X Zhu","year":"2021","unstructured":"Zhu, X., Zhu, L., Guo, J., Liang, S., & Dietze, S. (2021). Gl-gcn: global and local dependency guided graph convolutional networks for aspect-based sentiment classification. Expert Systems with Applications, 186, 115712. https:\/\/doi.org\/10.1016\/j.eswa.2021.115712.","journal-title":"Expert Systems with Applications"}],"container-title":["Journal of Intelligent Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-022-00729-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10844-022-00729-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-022-00729-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T05:58:37Z","timestamp":1676613517000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10844-022-00729-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,30]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["729"],"URL":"https:\/\/doi.org\/10.1007\/s10844-022-00729-1","relation":{},"ISSN":["0925-9902","1573-7675"],"issn-type":[{"value":"0925-9902","type":"print"},{"value":"1573-7675","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,30]]},"assertion":[{"value":"2 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 July 2022","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 conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}