{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T17:41:30Z","timestamp":1758044490930,"version":"3.44.0"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032046130","type":"print"},{"value":"9783032046147","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T00:00:00Z","timestamp":1757721600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T00:00:00Z","timestamp":1757721600000},"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\/978-3-032-04614-7_22","type":"book-chapter","created":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T12:24:27Z","timestamp":1757679867000},"page":"392-409","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SemSyn-LCE: A Charge Prediction Method Based on\u00a0Semantic Syntactic Fusion and\u00a0Legal Constituent Elements Matching"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6209-2527","authenticated-orcid":false,"given":"Wenjun","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6580-8025","authenticated-orcid":false,"given":"Bianxia","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7170-6625","authenticated-orcid":false,"given":"Wenhui","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6483-1431","authenticated-orcid":false,"given":"Qiao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7358-7426","authenticated-orcid":false,"given":"Yupeng","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,13]]},"reference":[{"key":"22_CR1","unstructured":"Al-Fedaghi, S.: Diagrammatic modelling of causality and causal relations (2023)"},{"key":"22_CR2","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.93","volume":"2","author":"N Aletras","year":"2016","unstructured":"Aletras, N., Tsarapatsanis, D., Preo\u0163iuc-Pietro, D., Lampos, V.: Predicting judicial decisions of the European court of human rights: a natural language processing perspective. PeerJ Comput. Sci. 2, e93 (2016)","journal-title":"PeerJ Comput. Sci."},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Aletras, N., Androutsopoulos, I.: LEGAL-BERT: the Muppets straight out of law school. In: Findings of the Association for Computational Linguistics, EMNLP 2020 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.261"},{"key":"22_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Y., Rohrbach, M., Yan, Z., Shuicheng, Y., Feng, J., Kalantidis, Y.: Graph-based global reasoning networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 433\u2013442 (2019)","DOI":"10.1109\/CVPR.2019.00052"},{"issue":"2","key":"22_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3424671","volume":"15","author":"Y Feng","year":"2021","unstructured":"Feng, Y., Li, C., Ge, J., Luo, B., Ng, V.: Recommending statutes: a portable method based on neural networks. ACM Trans. Knowl. Disc. Data (TKDD) 15(2), 1\u201322 (2021)","journal-title":"ACM Trans. Knowl. Disc. Data (TKDD)"},{"key":"22_CR6","first-page":"123","volume":"2","author":"VN Gagnon","year":"1966","unstructured":"Gagnon, V.N.: Legal reasoning in judicial decision making. Portia LJ 2, 123 (1966)","journal-title":"Portia LJ"},{"issue":"1","key":"22_CR7","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1109\/TNNLS.2022.3172588","volume":"35","author":"J Gan","year":"2022","unstructured":"Gan, J., et al.: Multigraph fusion for dynamic graph convolutional network. IEEE Trans. Neural Netw. Learn. Syst. 35(1), 196\u2013207 (2022)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"22_CR8","unstructured":"Hamilton, W., Ying, Z., Leskovec, J.: Inductive representation learning on large graphs. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"key":"22_CR9","unstructured":"Hu, Z., Li, X., Tu, C., Liu, Z., Sun, M.: Few-shot charge prediction with discriminative legal attributes. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 487\u2013498 (2018)"},{"key":"22_CR10","doi-asserted-by":"crossref","unstructured":"Huang, D., Lin, W.: A model for legal judgment prediction based on multi-model fusion. In: 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE), pp. 892\u2013895. IEEE (2019)","DOI":"10.1109\/EITCE47263.2019.9094946"},{"issue":"7","key":"22_CR11","doi-asserted-by":"publisher","first-page":"172104","DOI":"10.1007\/s11432-021-3367-y","volume":"65","author":"Z Ji","year":"2022","unstructured":"Ji, Z., Chen, K., He, Y., Pang, Y., Li, X.: Heterogeneous memory enhanced graph reasoning network for cross-modal retrieval. Sci. China Inf. Sci. 65(7), 172104 (2022)","journal-title":"Sci. China Inf. Sci."},{"key":"22_CR12","doi-asserted-by":"crossref","unstructured":"Johnson, R., Zhang, T.: Deep pyramid convolutional neural networks for text categorization. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 562\u2013570 (2017)","DOI":"10.18653\/v1\/P17-1052"},{"key":"22_CR13","unstructured":"Le, Y., He, C., Chen, M., Wu, Y., He, X., Zhou, B.: Learning to predict charges for legal judgment via self-attentive capsule network. In: ECAI 2020 (2020)"},{"issue":"1","key":"22_CR14","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1007\/s11280-021-00873-8","volume":"25","author":"L Li","year":"2022","unstructured":"Li, L., Zhao, L., Nai, P., Tao, X.: Charge prediction modeling with interpretation enhancement driven by double-layer criminal system. World Wide Web 25(1), 381\u2013400 (2022)","journal-title":"World Wide Web"},{"key":"22_CR15","doi-asserted-by":"crossref","unstructured":"Liu, Y., et al.: ML-LJP: multi-law aware legal judgment prediction. In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1023\u20131034 (2023)","DOI":"10.1145\/3539618.3591731"},{"key":"22_CR16","doi-asserted-by":"crossref","unstructured":"Liu, Y., Feng, S., Wang, D., Song, K., Ren, F., Zhang, Y.: A graph reasoning network for multi-turn response selection via customized pre-training. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 13433\u201313442 (2021)","DOI":"10.1609\/aaai.v35i15.17585"},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Luo, B., Feng, Y., Xu, J., Zhang, X., Zhao, D.: Learning to predict charges for criminal cases with legal basis. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2017)","DOI":"10.18653\/v1\/D17-1289"},{"key":"22_CR18","unstructured":"Niepert, M., Ahmed, M., Kutzkov, K.: Learning convolutional neural networks for graphs. In: International Conference on Machine Learning, pp. 2014\u20132023. PMLR (2016)"},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Pan, W., Chen, Y., Liu, Z., Li, X., Xu, Z.: Circumstance-aware graph neural network for legal judgment prediction. In: 2023 International Conference on Asian Language Processing (IALP), pp. 332\u2013337. IEEE (2023)","DOI":"10.1109\/IALP61005.2023.10337257"},{"key":"22_CR20","doi-asserted-by":"crossref","unstructured":"Pan, W., Chen, Y., Liu, Z., Li, X., Xu, Z.: Circumstance-aware graph neural network for legal judgment prediction. In: 2023 International Conference on Asian Language Processing (IALP), pp. 332\u2013337. IEEE (2023)","DOI":"10.1109\/IALP61005.2023.10337257"},{"key":"22_CR21","unstructured":"Petar, V., Guillem, C., Arantxa, C., Adriana, R., Pietro, L., Yoshua, B.: Graph attention networks. In: International Conference on Learning Representations, vol.\u00a08 (2018)"},{"key":"22_CR22","doi-asserted-by":"crossref","unstructured":"Shen, Y., Sun, J., Li, X., Zhang, L., Li, Y., Shen, X.: Legal article-aware end-to-end memory network for charge prediction. In: Proceedings of the 2nd International Conference on Computer Science and Application Engineering, pp.\u00a01\u20135 (2018)","DOI":"10.1145\/3207677.3278068"},{"key":"22_CR23","doi-asserted-by":"crossref","unstructured":"Sukanya, G., Priyadarshini, J.: A meta analysis of attention models on legal judgment prediction system. Int. J. Adv. Comput. Sci. Appl. 12(2) (2021)","DOI":"10.14569\/IJACSA.2021.0120266"},{"issue":"3","key":"22_CR24","doi-asserted-by":"publisher","first-page":"103663","DOI":"10.1016\/j.ipm.2024.103663","volume":"61","author":"S Tong","year":"2024","unstructured":"Tong, S., Yuan, J., Zhang, P., Li, L.: Legal judgment prediction via graph boosting with constraints. Inf. Process. Manage. 61(3), 103663 (2024)","journal-title":"Inf. Process. Manage."},{"key":"22_CR25","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Li\u00f2, P., Bengio, Y.: Graph attention networks. In: International Conference on Learning Representations (2018)"},{"key":"22_CR26","doi-asserted-by":"crossref","unstructured":"Wang, J., Le, Y., Cao, D., Lu, S., Quan, Z., Wang, M.: Graph reasoning with supervised contrastive learning for legal judgment prediction. IEEE Trans. Neural Netw. Learn. Syst. (2024)","DOI":"10.1109\/TNNLS.2023.3344634"},{"key":"22_CR27","unstructured":"Xiao, C., et\u00a0al.: CAIL2018: a large-scale legal dataset for judgment prediction (2018)"},{"key":"22_CR28","doi-asserted-by":"crossref","unstructured":"Xu, N., Wang, P., Chen, L., Pan, L., Wang, X., Zhao, J.: Distinguish confusing law articles for legal judgment prediction. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.acl-main.280"},{"key":"22_CR29","doi-asserted-by":"crossref","unstructured":"Yang, B., Chen, G., Luo, X.: A legal judgment prediction model based on BERT, attention, and graph convolutional network. In: 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 303\u2013310. IEEE (2024)","DOI":"10.1109\/ICTAI62512.2024.00052"},{"key":"22_CR30","doi-asserted-by":"crossref","unstructured":"Yang, W., Jia, W., Zhou, X., Luo, Y.: Legal judgment prediction via multi-perspective bi-feedback network. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence, pp. 4085\u20134091 (2019)","DOI":"10.24963\/ijcai.2019\/567"},{"key":"22_CR31","doi-asserted-by":"crossref","unstructured":"Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1480\u20131489 (2016)","DOI":"10.18653\/v1\/N16-1174"},{"issue":"1","key":"22_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40649-019-0069-y","volume":"6","author":"S Zhang","year":"2019","unstructured":"Zhang, S., Tong, H., Xu, J., Maciejewski, R.: Graph convolutional networks: a comprehensive review. Comput. Soc. Netw. 6(1), 1\u201323 (2019). https:\/\/doi.org\/10.1186\/s40649-019-0069-y","journal-title":"Comput. Soc. Netw."},{"key":"22_CR33","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Sa, R., Li, Y., Ge, F., Yu, H., Wang, S.: EK-CPSG: enhancing confusing charge prediction with criminal charge definition. In: 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 3595\u20133601. IEEE (2024)","DOI":"10.1109\/SMC54092.2024.10831612"},{"key":"22_CR34","doi-asserted-by":"crossref","unstructured":"Zhao, J., Guan, Z., Xu, C., Zhao, W., Chen, E.: Charge prediction by constitutive elements matching of crimes. In: IJCAI, pp. 4517\u20134523 (2022)","DOI":"10.24963\/ijcai.2022\/627"},{"issue":"5","key":"22_CR35","doi-asserted-by":"publisher","first-page":"103455","DOI":"10.1016\/j.ipm.2023.103455","volume":"60","author":"Q Zhao","year":"2023","unstructured":"Zhao, Q., Gao, T., Guo, N.: LA-MGFM: a legal judgment prediction method via Sememe-enhanced graph neural networks and multi-graph fusion mechanism. Inf. Process. Manage. 60(5), 103455 (2023)","journal-title":"Inf. Process. Manage."},{"key":"22_CR36","doi-asserted-by":"crossref","unstructured":"Zhong, H., Guo, Z., Tu, C., Xiao, C., Liu, Z., Sun, M.: Legal judgment prediction via topological learning. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3540\u20133549 (2018)","DOI":"10.18653\/v1\/D18-1390"}],"container-title":["Lecture Notes in Computer Science","Document Analysis and Recognition \u2013 ICDAR 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-04614-7_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T12:24:45Z","timestamp":1757679885000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-04614-7_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,13]]},"ISBN":["9783032046130","9783032046147"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-04614-7_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,13]]},"assertion":[{"value":"13 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Document Analysis and Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuhan","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":"16 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icdar2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iapr.org\/icdar2025","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}