{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T19:09:53Z","timestamp":1743016193732,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":29,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819608461"},{"type":"electronic","value":"9789819608478"}],"license":[{"start":{"date-parts":[[2024,12,14]],"date-time":"2024-12-14T00:00:00Z","timestamp":1734134400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,14]],"date-time":"2024-12-14T00:00:00Z","timestamp":1734134400000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-0847-8_8","type":"book-chapter","created":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T04:26:06Z","timestamp":1734063966000},"page":"113-126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Relation Extraction Method Based on Multi-layer Index and Cascading Binary Framework"],"prefix":"10.1007","author":[{"given":"Wanting","family":"Ji","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keyan","family":"Wen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linlin","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baoyan","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,14]]},"reference":[{"key":"8_CR1","unstructured":"Haihong, E., et al.: Survey of entity relationship extraction based on deep learning. J. Softw. 30(6) (2019)"},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"Zhang, S., Wang, X., Chen, Z., Wang, L., Xu, D., Jia, Y.: Survey of supervised joint entity relation extraction methods. J. Front. Comput. Sci. Technol. 16(4) (2022)","DOI":"10.1007\/s11704-021-0474-x"},{"key":"8_CR3","unstructured":"Socher, R., Huval, B., Manning, C.D., Ng, A.Y.: Semantic compositionality through recursive matrix-vector spaces. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 1201\u20131211 (2012)"},{"key":"8_CR4","unstructured":"Zeng, D., Liu, K., Lai, S., Zhou, G., Zhao, J.: Relation classification via convolutional deep neural network. In: Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, pp. 2335\u20132344 (2014)"},{"key":"8_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103579","volume":"136","author":"K Ahmed","year":"2024","unstructured":"Ahmed, K., Khurshid, S.K., Hina, S.: CyberEntRel: joint extraction of cyber entities and relations using deep learning. Comput. Secur. 136, 103579 (2024)","journal-title":"Comput. Secur."},{"key":"8_CR6","doi-asserted-by":"crossref","unstructured":"Sui, D., Zeng, X., Chen, Y., Liu, K., Zhao, J.: Joint entity and relation extraction with set prediction networks. In: IEEE Transactions on Neural Networks and Learning Systems (2023)","DOI":"10.1109\/TNNLS.2023.3264735"},{"key":"8_CR7","doi-asserted-by":"crossref","unstructured":"Vu, N.T., Adel, H., Gupta, P., Sch\u00fctze, H.: Combining recurrent and convolutional neural networks for relation classification. arXiv:1605.07333 (2016)","DOI":"10.18653\/v1\/N16-1065"},{"key":"8_CR8","unstructured":"Zhang, S., Zheng, D., Hu, X., Yang, M.: Bidirectional long short-term memory networks for relation classification. In: Proceedings of the 29th Pacific Asia Conference on Language, Information, and Computation, pp. 73\u201378 (2015)"},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Mintz, M., Bills, S., Snow, R., Jurafsky, D.: Distant supervision for relation extraction without labeled data. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, pp. 1003\u20131011","DOI":"10.3115\/1690219.1690287"},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Gormley, M.R., Yu, M., Dredze, M.: Improved relation extraction with feature-rich compositional embedding models. arXiv:1505.02419 (2015)","DOI":"10.18653\/v1\/D15-1205"},{"issue":"1","key":"8_CR11","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1075\/li.30.1.03nad","volume":"30","author":"D Nadeau","year":"2007","unstructured":"Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvisticae Investigationes 30(1), 3\u201326 (2007)","journal-title":"Lingvisticae Investigationes"},{"key":"8_CR12","first-page":"1","volume":"2","author":"N Bach","year":"2007","unstructured":"Bach, N., Badaskar, S.: A review of relation extraction. Lit. Rev. Lang. Stat. II 2, 1\u201315 (2007)","journal-title":"Lit. Rev. Lang. Stat. II"},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Wei, Z., Su, J., Wang, Y., Tian, Y., Chang, Y.: A novel cascade binary tagging framework for relational triple extraction. arXiv:1909.03227 (2019)","DOI":"10.18653\/v1\/2020.acl-main.136"},{"key":"8_CR14","doi-asserted-by":"crossref","unstructured":"Zheng, H., et al.: PRGC: potential relation and global correspondence based joint relational triple extraction. arXiv:2106.09895 (2021)","DOI":"10.18653\/v1\/2021.acl-long.486"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"Wang, Y., Yu, B., Zhang, Y., Liu, T., Zhu, H., Sun, L.: TPLinker: single-stage joint extraction of entities and relations through token pair linking. arXiv:2010.13415 (2020)","DOI":"10.18653\/v1\/2020.coling-main.138"},{"issue":"10","key":"8_CR16","doi-asserted-by":"publisher","first-page":"11285","DOI":"10.1609\/aaai.v36i10.21379","volume":"36","author":"Y-M Shang","year":"2022","unstructured":"Shang, Y.-M., Huang, H., Mao, X.: Onerel: Joint entity and relation extraction with one module in one step. Proc. AAAI Conf. Artif. Intell. 36(10), 11285\u201311293 (2022). https:\/\/doi.org\/10.1609\/aaai.v36i10.21379","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"8_CR17","doi-asserted-by":"crossref","unstructured":"Fu, T.J., Li, P.H., Ma, W.Y.: Graphrel: modeling text as relational graphs for joint entity and relation extraction. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 1409\u20131418 (2019)","DOI":"10.18653\/v1\/P19-1136"},{"key":"8_CR18","doi-asserted-by":"crossref","unstructured":"Katiyar, A., Cardie, C.: Going out on a limb: joint extraction of entity mentions and relations without dependency trees. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 917\u2013928 (2017)","DOI":"10.18653\/v1\/P17-1085"},{"issue":"16","key":"8_CR19","doi-asserted-by":"publisher","first-page":"14257","DOI":"10.1609\/aaai.v35i16.17677","volume":"35","author":"H Ye","year":"2021","unstructured":"Ye, H., et al.: Contrastive triple extraction with generative transformer. Proc. AAAI Conf. Artif. Intell. 35(16), 14257\u201314265 (2021). https:\/\/doi.org\/10.1609\/aaai.v35i16.17677","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"8_CR20","unstructured":"Rao, D., Li, R.: Chinese entity relationship extraction method based on schema enhancement. Softw. Guide 22(2) (2023)"},{"key":"8_CR21","doi-asserted-by":"crossref","unstructured":"Zheng, S., Wang, F., Bao, H., Hao, Y., Zhou, P., Xu, B.: Joint extraction of entities and relations based on a novel tagging scheme. arXiv:1706.05075 (2017)","DOI":"10.18653\/v1\/P17-1113"},{"key":"8_CR22","doi-asserted-by":"crossref","unstructured":"Zeng, X., Zeng, D., He, S., Liu, K., Zhao, J.: Extracting relational facts by an end-to-end neural model with copy mechanism. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 506\u2013514 (2018)","DOI":"10.18653\/v1\/P18-1047"},{"key":"8_CR23","unstructured":"Ma, L., Ren, H., Zhang, X.: Effective cascade dual-decoder model for joint entity and relation extraction. arXiv:2106.14163 (2021)"},{"key":"8_CR24","doi-asserted-by":"crossref","unstructured":"Yuan, Y., Zhou, X., Pan, S., Zhu, Q., Song, Z., Guo, L.: A relation-specific attention network for joint entity and relation extraction. In: International Joint Conference on Artificial Intelligence (2021)","DOI":"10.24963\/ijcai.2020\/561"},{"key":"8_CR25","unstructured":"Zheng, Z., Han, D., Zhao, H.: Joint extraction of entities and relations model for single-step span-labeling. Comput. Eng. Appl. 1\u201311 (2022)"},{"issue":"2","key":"8_CR26","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0281055","volume":"18","author":"D Han","year":"2023","unstructured":"Han, D., Zheng, Z., Zhao, H., Feng, S., Pang, H.: Span-based single-stage joint entity-relation extraction model. PLoS ONE 18(2), e0281055 (2023)","journal-title":"PLoS ONE"},{"key":"8_CR27","doi-asserted-by":"crossref","unstructured":"Li, X., Luo, X., Dong, C., Yang, D., Luan, B., He, Z.: TDEER: an efficient translating decoding schema for joint extraction of entities and relations. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 8055\u20138064 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.635"},{"key":"8_CR28","doi-asserted-by":"crossref","unstructured":"Ren, F., et al.: A novel global feature-oriented relational triple extraction model based on table filling. arXiv:2109.06705 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.208"},{"key":"8_CR29","doi-asserted-by":"crossref","unstructured":"Xu, B., et al.: EmRel: joint representation of entities and embedded relations for multi-triple extraction. In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 659\u2013665 (2022)","DOI":"10.18653\/v1\/2022.naacl-main.48"}],"container-title":["Lecture Notes in Computer Science","Advanced Data Mining and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0847-8_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T05:04:07Z","timestamp":1734066247000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0847-8_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,14]]},"ISBN":["9789819608461","9789819608478"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0847-8_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,14]]},"assertion":[{"value":"14 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors declare that they have no conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interests"}},{"value":"ADMA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Data Mining and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"adma2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/adma2024.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}