{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T19:31:34Z","timestamp":1758396694524,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031683220"},{"type":"electronic","value":"9783031683237"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-68323-7_11","type":"book-chapter","created":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T07:02:18Z","timestamp":1723878138000},"page":"129-146","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploring Causal Chain Identification: Comprehensive Insights from\u00a0Text and\u00a0Knowledge Graphs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1081-0475","authenticated-orcid":false,"given":"Ziwei","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryutaro","family":"Ichise","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,18]]},"reference":[{"key":"11_CR1","doi-asserted-by":"publisher","first-page":"10064","DOI":"10.3390\/app112110064","volume":"11","author":"W Ali","year":"2021","unstructured":"Ali, W., Zuo, W., Ali, R., Zuo, X., Rahman, G.: Causality mining in natural languages using machine and deep learning techniques: a survey. Appl. Sci. 11, 10064 (2021)","journal-title":"Appl. Sci."},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Chu, Z., Huang, J., Li, R., Chu, W., Li, S.: Causal effect estimation: recent advances, challenges, and opportunities (2023)","DOI":"10.1007\/978-3-031-35051-1_5"},{"key":"11_CR3","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics, pp. 4171\u20134186 (2019)"},{"key":"11_CR4","unstructured":"He, P., Liu, X., Gao, J., Chen, W.: DeBERTa: decoding-enhanced BERT with disentangled attention. In: International Conference on Learning Representations (2021)"},{"key":"11_CR5","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional LSTM-CRF models for sequence tagging. arXiv (2015)"},{"key":"11_CR6","unstructured":"Johansson, F.D., Shalit, U., Sontag, D.: Learning representations for counterfactual inference. In: Proceedings of the 33rd International Conference on International Conference on Machine Learning, vol. 48, pp. 3020\u20133029 (2016)"},{"key":"11_CR7","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. In: Proceeding of the 2nd International Conference on Learning Representations (2014)"},{"issue":"7553","key":"11_CR8","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.E.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"issue":"2","key":"11_CR9","doi-asserted-by":"publisher","first-page":"167","DOI":"10.3233\/SW-140134","volume":"6","author":"J Lehmann","year":"2015","unstructured":"Lehmann, J., et al.: DBpedia - a large-scale, multilingual knowledge base extracted from Wikipedia. Semant. Web 6(2), 167\u2013195 (2015)","journal-title":"Semant. Web"},{"key":"11_CR10","unstructured":"Louizos, C., Shalit, U., Mooij, J., Sontag, D., Zemel, R., Welling, M.: Causal effect inference with deep latent-variable models. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 6449\u20136459 (2017)"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Miller, G.A.: WordNet: a lexical database for English. In: Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey (1994)","DOI":"10.3115\/1075812.1075938"},{"key":"11_CR12","unstructured":"OpenAI, et\u00a0al., J.A.: GPT-4 technical report (2024)"},{"key":"11_CR13","unstructured":"Sohn, K., Yan, X., Lee, H.: Learning structured output representation using deep conditional generative models. In: Proceedings of the 28th International Conference on Neural Information Processing Systems, pp. 3483\u20133491 (2015)"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Speer, R., Chin, J., Havasi, C.: Conceptnet 5.5: an open multilingual graph of general knowledge. In: Proceedings of the 31st Conference on Artificial Intelligence, pp. 4444\u20134451 (2017)","DOI":"10.1609\/aaai.v31i1.11164"},{"key":"11_CR15","unstructured":"Tan, F.A., Ng, S.K.: NUS-IDS at FinCausal 2021: dependency tree in graph neural network for better cause-effect span detection. In: Proceedings of the 3rd Financial Narrative Processing Workshop, pp. 37\u201343. Association for Computational Linguistics (2021)"},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Williams, A., Nangia, N., Bowman, S.: A broad-coverage challenge corpus for sentence understanding through inference. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1112\u20131122 (2018)","DOI":"10.18653\/v1\/N18-1101"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Xiong, K., et al.: ReCo: reliable causal chain reasoning via structural causal recurrent neural networks. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 6426\u20136438 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.431"},{"key":"11_CR18","unstructured":"Xu, Z., Nararatwong, R., Kertkeidkachorn, N., Ichise, R.: iLab at fincausal 2022: enhancing causality detection with an external cause-effect knowledge graph. In: Proceedings of the 4th Financial Narrative Processing Workshop, pp. 124\u2013127 (2022)"},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Xu, Z., Takamura, H., Ichise, R.: A framework to construct financial causality knowledge graph from text. In: 2024 IEEE 18th International Conference on Semantic Computing, pp. 57\u201364 (2024)","DOI":"10.1109\/ICSC59802.2024.00015"}],"container-title":["Lecture Notes in Computer Science","Big Data Analytics and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-68323-7_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T07:03:51Z","timestamp":1723878231000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-68323-7_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031683220","9783031683237"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-68323-7_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"18 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DaWaK","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Big Data Analytics and Knowledge Discovery","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Naples","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"26 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dawak2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.dexa.org\/dawak2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}