{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:22:21Z","timestamp":1766067741644,"version":"3.40.3"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031306716"},{"type":"electronic","value":"9783031306723"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-30672-3_48","type":"book-chapter","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T11:10:49Z","timestamp":1681384249000},"page":"716-731","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["HIT - An Effective Approach to\u00a0Build a\u00a0Dynamic Financial Knowledge Base"],"prefix":"10.1007","author":[{"given":"Xinyi","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Xin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanyan","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,4,14]]},"reference":[{"key":"48_CR1","doi-asserted-by":"crossref","unstructured":"Agichtein, E., Gravano, L.: Snowball: Extracting relations from large plain-text collections. In: Proceedings of the Fifth ACM Conference on Digital Libraries, June 2\u20137, 2000, San Antonio, TX, pp. 85\u201394. ACM (2000)","DOI":"10.1145\/376284.375774"},{"key":"48_CR2","unstructured":"Banko, M., Etzioni, O.: The tradeoffs between open and traditional relation extraction. In: McKeown, K.R., Moore, J.D., Teufel, S., Allan, J., Furui, S. (eds.) ACL 2008, Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics, June 15\u201320, 2008, Columbus, Ohio, pp. 28\u201336. The Association for Computer Linguistics (2008)"},{"key":"48_CR3","doi-asserted-by":"crossref","unstructured":"Blum, A., Mitchell, T.M.: Combining labeled and unlabeled data with co-training. In: Bartlett, P.L., Mansour, Y. (eds.) Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT 1998, Madison, Wisconsin, July 24\u201326, 1998, pp. 92\u2013100. ACM (1998)","DOI":"10.1145\/279943.279962"},{"key":"48_CR4","doi-asserted-by":"publisher","unstructured":"Brin, S.: Extracting patterns and relations from the world wide web. In: Atzeni, P., Mendelzon, A., Mecca, G. (eds.) WebDB 1998. LNCS, vol. 1590, pp. 172\u2013183. Springer, Heidelberg (1999). https:\/\/doi.org\/10.1007\/10704656_11","DOI":"10.1007\/10704656_11"},{"key":"48_CR5","unstructured":"Bunescu, R.C., Mooney, R.J.: Learning to extract relations from the web using minimal supervision. In: Carroll, J.A., van den Bosch, A., Zaenen, A. (eds.) ACL 2007, Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics, June 23\u201330, 2007, Prague. The Association for Computational Linguistics (2007)"},{"key":"48_CR6","unstructured":"Chan, Y.S., Roth, D.: Exploiting syntactico-semantic structures for relation extraction. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp. 551\u2013560 (2011)"},{"key":"48_CR7","doi-asserted-by":"crossref","unstructured":"Cheng, D., Yang, F., Wang, X., Zhang, Y., Zhang, L.: Knowledge graph-based event embedding framework for financial quantitative investments. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 2221\u20132230 (2020)","DOI":"10.1145\/3397271.3401427"},{"key":"48_CR8","unstructured":"Craven, M., Kumlien, J.: Constructing biological knowledge bases by extracting information from text sources. In: Lengauer, T., et al. (eds.) Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology, August 6\u201310, 1999, Heidelberg, pp. 77\u201386. AAAI (1999)"},{"key":"48_CR9","doi-asserted-by":"crossref","unstructured":"Dong, X.L., et al.: From data fusion to knowledge fusion. PVLDB 7(10), 881\u2013892 (2015)","DOI":"10.14778\/2732951.2732962"},{"key":"48_CR10","doi-asserted-by":"crossref","unstructured":"Elhammadi, S., et al.: A high precision pipeline for financial knowledge graph construction. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 967\u2013977 (2020)","DOI":"10.18653\/v1\/2020.coling-main.84"},{"key":"48_CR11","doi-asserted-by":"crossref","unstructured":"Guo, K., Jiang, T., Zhang, H.: Knowledge graph enhanced event extraction in financial documents. In: 2020 IEEE International Conference on Big Data (Big Data), pp. 1322\u20131329. IEEE (2020)","DOI":"10.1109\/BigData50022.2020.9378471"},{"key":"48_CR12","doi-asserted-by":"crossref","unstructured":"Han, X., Sun, L., Zhao, J.: Collective entity linking in web text: A graph-based method. In: Ma, W., Nie, J., Baeza-Yates, R., Chua, T., Croft, W.B. (eds.) Proceeding of the SIGIR, pp. 765\u2013774 (2011)","DOI":"10.1145\/2009916.2010019"},{"key":"48_CR13","doi-asserted-by":"crossref","unstructured":"Han, X., Gao, T., Yao, Y., Ye, D., Liu, Z., Sun, M.: Opennre: An open and extensible toolkit for neural relation extraction. In: Proceedings of the EMNLP-IJCNLP, pp. 169\u2013174 (2019)","DOI":"10.18653\/v1\/D19-3029"},{"key":"48_CR14","doi-asserted-by":"crossref","unstructured":"Hasegawa, T., Sekine, S., Grishman, R.: Discovering relations among named entities from large corpora. In: Scott, D., Daelemans, W., Walker, M.A. (eds.) Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, 21\u201326 July, 2004, Barcelona, pp. 415\u2013422. ACL (2004)","DOI":"10.3115\/1218955.1219008"},{"key":"48_CR15","doi-asserted-by":"crossref","unstructured":"Kambhatla, N.: Combining lexical, syntactic, and semantic features with maximum entropy models for information extraction. In: Proceedings of the ACL Interactive Poster and Demonstration Sessions, pp. 178\u2013181 (2004)","DOI":"10.3115\/1219044.1219066"},{"key":"48_CR16","doi-asserted-by":"crossref","unstructured":"Lin, X., Chen, L.: Domain-aware multi-truth discovery from conflicting sources. Proceedings of the VLDB Endowment (2018)","DOI":"10.1145\/3187009.3177739"},{"key":"48_CR17","doi-asserted-by":"crossref","unstructured":"Miao, R., Zhang, X., Yan, H., Chen, C.: A dynamic financial knowledge graph based on reinforcement learning and transfer learning. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 5370\u20135378. IEEE (2019)","DOI":"10.1109\/BigData47090.2019.9005691"},{"key":"48_CR18","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 (2009)","DOI":"10.3115\/1690219.1690287"},{"key":"48_CR19","unstructured":"Mooney, R., Bunescu, R.: Subsequence kernels for relation extraction. Adv. Neural Inf. Process. Syst. 18 (2005)"},{"key":"48_CR20","unstructured":"Muslea, I., Minton, S., Knoblock, C.A.: Selective sampling with redundant views. In: Kautz, H.A., Porter, B.W. (eds.) Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30\u2013August 3, 2000, Austin, Texas, pp. 621\u2013626. AAAI Press\/The MIT Press (2000)"},{"key":"48_CR21","unstructured":"Pawar, S., Palshikar, G.K., Bhattacharyya, P.: Relation extraction: A survey. arXiv preprint arXiv:1712.05191 (2017)"},{"key":"48_CR22","doi-asserted-by":"crossref","unstructured":"Pochampally, R., Sarma, A.D., Dong, X.L., Meliou, A., Srivastava, D.: Fusing data with correlations. In: Dyreson, C.E., Li, F., \u00d6zsu, M.T. (eds.) International Conference on Management of Data, SIGMOD 2014, Snowbird, UT, June 22\u201327, 2014, pp. 433\u2013444. ACM (2014)","DOI":"10.1145\/2588555.2593674"},{"key":"48_CR23","doi-asserted-by":"crossref","unstructured":"Ratner, A., Bach, S.H., Ehrenberg, H., Fries, J., Wu, S., R\u00e9, C.: Snorkel: Rapid training data creation with weak supervision. In: Proceedings of the VLDB Endowment. International Conference on Very Large Data Bases, vol. 11, p. 269. NIH Public Access (2017)","DOI":"10.14778\/3157794.3157797"},{"key":"48_CR24","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1007\/978-3-642-15939-8_10","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"S Riedel","year":"2010","unstructured":"Riedel, S., Yao, L., McCallum, A.: Modeling relations and their mentions without labeled text. In: Balc\u00e1zar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010. LNCS (LNAI), vol. 6323, pp. 148\u2013163. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15939-8_10"},{"key":"48_CR25","doi-asserted-by":"crossref","unstructured":"Sun, A., Grishman, R.: Active learning for relation type extension with local and global data views. In: Chen, X., Lebanon, G., Wang, H., Zaki, M.J. (eds.) 21st ACM International Conference on Information and Knowledge Management, CIKM\u201912, Maui, HI, October 29\u2013November 02, 2012, pp. 1105\u20131112. ACM (2012)","DOI":"10.1145\/2396761.2398409"},{"issue":"1","key":"48_CR26","first-page":"35","volume":"28","author":"Y Tong","year":"2017","unstructured":"Tong, Y., Yuan, Y., Cheng, Y., Chen, L., Wang, G.: Survey on spatiotemporal crowdsourced data management techniques. J. Softw. 28(1), 35\u201358 (2017)","journal-title":"J. Softw."},{"key":"48_CR27","doi-asserted-by":"crossref","unstructured":"Vyas, V., Pantel, P., Crestan, E.: Helping editors choose better seed sets for entity set expansion. In: Cheung, D.W., Song, I., Chu, W.W., Hu, X., Lin, J. (eds.) Proceedings of the 18th ACM Conference on Information and Knowledge Management, CIKM 2009, Hong Kong, China, November 2\u20136, 2009, pp. 225\u2013234. ACM (2009)","DOI":"10.1145\/1645953.1645984"},{"issue":"4","key":"48_CR28","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1145\/1519103.1519113","volume":"37","author":"DS Weld","year":"2008","unstructured":"Weld, D.S., Hoffmann, R., Wu, F.: Using wikipedia to bootstrap open information extraction. SIGMOD Rec. 37(4), 62\u201368 (2008)","journal-title":"SIGMOD Rec."},{"key":"48_CR29","doi-asserted-by":"crossref","unstructured":"Yan, Y., Okazaki, N., Matsuo, Y., Yang, Z., Ishizuka, M.: Unsupervised relation extraction by mining Wikipedia texts using information from the web. In: Su, K., Su, J., Wiebe, J. (eds.) ACL 2009, Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the AFNLP, 2\u20137 August 2009, Singapore, pp. 1021\u20131029. The Association for Computer Linguistics (2009)","DOI":"10.3115\/1690219.1690289"},{"key":"48_CR30","doi-asserted-by":"crossref","unstructured":"Yang, S., et al.: Financial risk analysis for SMES with graph-based supply chain mining. In: Proceedings of the IJCAI, pp. 4661\u20134667 (2020)","DOI":"10.24963\/ijcai.2020\/643"},{"key":"48_CR31","doi-asserted-by":"crossref","unstructured":"Yang, Y., Miao, Z., Gao, J., Lu, J., Shi, G.: Automatic Chinese financial knowledge graph constructing framework. In: Proceedings of the ACAI, pp. 18:1\u201318:9 (2021)","DOI":"10.1145\/3508546.3508564"},{"key":"48_CR32","doi-asserted-by":"crossref","unstructured":"Yang, Y., Miao, Z., Gao, J., Lu, J., Shi, G.: Automatic Chinese financial knowledge graph constructing framework. In: 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence, pp. 1\u20139 (2021)","DOI":"10.1145\/3508546.3508564"},{"issue":"6","key":"48_CR33","doi-asserted-by":"publisher","first-page":"550","DOI":"10.14778\/2168651.2168656","volume":"5","author":"B Zhao","year":"2012","unstructured":"Zhao, B., Rubinstein, B.I.P., Gemmell, J., Han, J.: A bayesian approach to discovering truth from conflicting sources for data integration. Proc. VLDB Endow. 5(6), 550\u2013561 (2012)","journal-title":"Proc. VLDB Endow."},{"key":"48_CR34","doi-asserted-by":"crossref","unstructured":"Zhou, G., Su, J., Zhang, J., Zhang, M.: Exploring various knowledge in relation extraction. In: Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL\u201905), pp. 427\u2013434 (2005)","DOI":"10.3115\/1219840.1219893"},{"key":"48_CR35","doi-asserted-by":"crossref","unstructured":"Zhou, P., et al.: Attention-based bidirectional long short-term memory networks for relation classification. In: Proceedings of the ACL. The Association for Computer Linguistics (2016)","DOI":"10.18653\/v1\/P16-2034"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-30672-3_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T06:39:44Z","timestamp":1729233584000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-30672-3_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031306716","9783031306723"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-30672-3_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"14 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.tjudb.cn\/dasfaa2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"652","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"125","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"66","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7.3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}