{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:08:11Z","timestamp":1743109691394,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031084720"},{"type":"electronic","value":"9783031084737"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08473-7_23","type":"book-chapter","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T18:03:10Z","timestamp":1655402590000},"page":"255-266","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Text Structural Analysis Model for\u00a0Address Extraction"],"prefix":"10.1007","author":[{"given":"Rishabh","family":"Kumar","sequence":"first","affiliation":[]},{"given":"Kamal","family":"Jakhar","sequence":"additional","affiliation":[]},{"given":"Hemant","family":"Tiwari","sequence":"additional","affiliation":[]},{"given":"Naresh","family":"Purre","sequence":"additional","affiliation":[]},{"given":"Priyanshu","family":"Kumar","sequence":"additional","affiliation":[]},{"given":"Jiban","family":"Prakash","sequence":"additional","affiliation":[]},{"given":"Vanraj","family":"Vala","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,6,13]]},"reference":[{"key":"23_CR1","doi-asserted-by":"publisher","unstructured":"Abid, N., ul Hasan, A., Shafait, F.: DeepParse: a trainable postal address parser. In: 2018 Digital Image Computing: Techniques and Applications (DICTA), pp. 1\u20138 (2018). https:\/\/doi.org\/10.1109\/DICTA.2018.8615844","DOI":"10.1109\/DICTA.2018.8615844"},{"key":"23_CR2","doi-asserted-by":"crossref","unstructured":"Adel, H., Sch\u00fctze, H.: Exploring different dimensions of attention for uncertainty detection. In: Proceedings of the 15th Conference of the Association for Computational Linguistics, pp. 22\u201334 (2017). https:\/\/aclanthology.org\/E17-1003","DOI":"10.18653\/v1\/E17-1003"},{"key":"23_CR3","doi-asserted-by":"publisher","unstructured":"Asahara, M., Matsumoto, Y.: Japanese named entity extraction with redundant morphological analysis. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, vol. 1, pp. 8\u201315 (2003). https:\/\/doi.org\/10.3115\/1073445.1073447","DOI":"10.3115\/1073445.1073447"},{"key":"23_CR4","doi-asserted-by":"publisher","unstructured":"Banerjee, P., Pal, K.K., Devarakonda, M., Baral, C.: Biomedical named entity recognition via knowledge guidance and question answering. ACM Trans. Comput. Healthcare 2(4) (2021). https:\/\/doi.org\/10.1145\/3465221","DOI":"10.1145\/3465221"},{"key":"23_CR5","doi-asserted-by":"publisher","unstructured":"Collobert, R., Weston, J.: A unified architecture for natural language processing: deep neural networks with multitask learning. In: Proceedings of the 25th International Conference on Machine Learning, pp. 160\u2013167. Association for Computing Machinery (2008). https:\/\/doi.org\/10.1145\/1390156.1390177","DOI":"10.1145\/1390156.1390177"},{"key":"23_CR6","doi-asserted-by":"crossref","unstructured":"Graf, T.M., Lemire, D.: Xor filters: faster and smaller than bloom and cuckoo filters. CoRR (2019). http:\/\/arxiv.org\/abs\/1912.08258","DOI":"10.1145\/3376122"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Grishman, R., Sundheim, B.: Message understanding conference- 6: a brief history. In: COLING 1996 Volume 1: The 16th International Conference on Computational Linguistics (1996). https:\/\/aclanthology.org\/C96-1079","DOI":"10.3115\/992628.992709"},{"key":"23_CR8","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional LSTM-CRF models for sequence tagging. CoRR (2015). http:\/\/arxiv.org\/abs\/1508.01991"},{"key":"23_CR9","doi-asserted-by":"crossref","unstructured":"Li, X., Feng, J., Meng, Y., Han, Q., Wu, F., Li, J.: A unified MRC framework for named entity recognition. CoRR (2019). http:\/\/arxiv.org\/abs\/1910.11476","DOI":"10.18653\/v1\/2020.acl-main.519"},{"key":"23_CR10","doi-asserted-by":"crossref","unstructured":"McCallum, A., Li, W.: Early results for named entity recognition with conditional random fields, feature induction and web-enhanced Lexicons. In: Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003, pp. 188\u2013191 (2003). https:\/\/aclanthology.org\/W03-0430","DOI":"10.3115\/1119176.1119206"},{"key":"23_CR11","doi-asserted-by":"publisher","unstructured":"Nesi, P., Pantaleo, G., Tenti, M.: Ge(o)lo(cator): geographic information extraction from unstructured text data and web documents. In: 2014 9th International Workshop on Semantic and Social Media Adaptation and Personalization, pp. 60\u201365 (2014). https:\/\/doi.org\/10.1109\/SMAP.2014.27","DOI":"10.1109\/SMAP.2014.27"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Rastogi, A., Zang, X., Sunkara, S., Gupta, R., Khaitan, P.: Towards scalable multi-domain conversational agents: the schema-guided dialogue dataset. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 8689\u20138696 (2020)","DOI":"10.1609\/aaai.v34i05.6394"},{"key":"23_CR13","unstructured":"Rau, L.F.: Extracting company names from text. In: Proceedings the Seventh IEEE Conference on Artificial Intelligence Application. IEEE Computer Society (1991)"},{"key":"23_CR14","doi-asserted-by":"publisher","unstructured":"Schmidt, S., Manschitz, S., Rensing, C., Steinmetz, R.: Extraction of address data from unstructured text using free knowledge resources. In: Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies (2013). https:\/\/doi.org\/10.1145\/2494188.2494193","DOI":"10.1145\/2494188.2494193"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Taghva, K., Coombs, J.S., Pereda, R., Nartker, T.A.: Address extraction using hidden Markov models. In: Document Recognition and Retrieval XII, vol. 5676, pp. 119\u2013126. International Society for Optics and Photonics (2005)","DOI":"10.1117\/12.587799"},{"key":"23_CR16","doi-asserted-by":"crossref","unstructured":"Vu, N.T., Adel, H., Gupta, P., Sch\u00fctze, H.: Combining recurrent and convolutional neural networks for relation classification. CoRR (2016). http:\/\/arxiv.org\/abs\/1605.07333","DOI":"10.18653\/v1\/N16-1065"},{"key":"23_CR17","unstructured":"Wick, M.: Geonames. http:\/\/www.geonames.org\/"},{"key":"23_CR18","unstructured":"Yassine, M., Beauchemin, D.: DeepParse: a state-of-the-art deep learning multinational addresses parser (2020). https:\/\/deepparse.org"},{"key":"23_CR19","unstructured":"Yin, W., Kann, K., Yu, M., Sch\u00fctze, H.: Comparative study of CNN and RNN for natural language processing. CoRR (2017). http:\/\/arxiv.org\/abs\/1702.01923"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08473-7_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T18:09:01Z","timestamp":1655402941000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08473-7_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031084720","9783031084737"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08473-7_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"13 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLDB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications of Natural Language to Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Valencia","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nldb2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/nldb2022.prhlt.upv.es\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"106","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":"28","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":"20","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":"26% - 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":"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)"}}]}}