{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T17:05:32Z","timestamp":1780592732475,"version":"3.54.1"},"publisher-location":"Cham","reference-count":41,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031194320","type":"print"},{"value":"9783031194337","type":"electronic"}],"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\/978-3-031-19433-7_47","type":"book-chapter","created":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T06:20:33Z","timestamp":1665901233000},"page":"827-844","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Knowledge Graph Induction Enabling Recommending and\u00a0Trend Analysis: A Corporate Research Community Use Case"],"prefix":"10.1007","author":[{"given":"Nandana","family":"Mihindukulasooriya","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mike","family":"Sava","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaetano","family":"Rossiello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md. Faisal Mahbub","family":"Chowdhury","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irene","family":"Yachbes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aditya","family":"Gidh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jillian","family":"Duckwitz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kovit","family":"Nisar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Santos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alfio","family":"Gliozzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,16]]},"reference":[{"issue":"6","key":"47_CR1","doi-asserted-by":"publisher","first-page":"3901","DOI":"10.1007\/s10462-019-09782-9","volume":"53","author":"FN Al-Aswadi","year":"2019","unstructured":"Al-Aswadi, F.N., Chan, H.Y., Gan, K.H.: Automatic ontology construction from text: a review from shallow to deep learning trend. Artif. Intell. Rev. 53(6), 3901\u20133928 (2019). https:\/\/doi.org\/10.1007\/s10462-019-09782-9","journal-title":"Artif. Intell. Rev."},{"key":"47_CR2","unstructured":"Albrecht, J., Belger, A., Blum, R., Zimmermann, R.: Business analytics on knowledge graphs for market trend analysis. In: LWDA, pp. 371\u2013376 (2019)"},{"key":"47_CR3","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1007\/978-3-030-55814-7_18","volume-title":"ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium","author":"S Angioni","year":"2020","unstructured":"Angioni, S., Salatino, A.A., Osborne, F., Recupero, D.R., Motta, E.: Integrating knowledge graphs for analysing academia and industry dynamics. In: Bellatreche, L., et al. (eds.) TPDL\/ADBIS -2020. CCIS, vol. 1260, pp. 219\u2013225. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-55814-7_18"},{"key":"47_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/978-3-030-86324-1_18","volume-title":"Linking Theory and Practice of Digital Libraries","author":"G Heidari","year":"2021","unstructured":"Heidari, G., Ramadan, A., Stocker, M., Auer, S.: Leveraging a federation of knowledge graphs to improve faceted search in\u00a0digital libraries. In: Berget, G., Hall, M.M., Brenn, D., Kumpulainen, S. (eds.) TPDL 2021. LNCS, vol. 12866, pp. 141\u2013152. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86324-1_18"},{"issue":"11","key":"47_CR5","first-page":"2215","volume":"66","author":"L Bornmann","year":"2015","unstructured":"Bornmann, L., Mutz, R.: Growth rates of modern science: a bibliometric analysis based on the number of publications and cited references. J. Am. Soc. Inf. Sci. 66(11), 2215\u20132222 (2015)","journal-title":"J. Am. Soc. Inf. Sci."},{"key":"47_CR6","unstructured":"Cabot, P.H., Navigli, R.: REBEL: relation extraction by end-to-end language generation. In: EMNLP (Findings), pp. 2370\u20132381. Association for Computational Linguistics (2021)"},{"key":"47_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117035","volume":"15","author":"X Cai","year":"2022","unstructured":"Cai, X., Xie, L., Tian, R., Cui, Z.: Explicable recommendation based on knowledge graph. Expert Syst. Appl. 15, 117035 (2022)","journal-title":"Expert Syst. Appl."},{"key":"47_CR8","doi-asserted-by":"crossref","unstructured":"Carlson, A., Betteridge, J., Kisiel, B., Settles, B., Hruschka Jr., E.R., Mitchell, T.M.: Toward an architecture for never-ending language learning. In: AAAI. AAAI Press (2010)","DOI":"10.1609\/aaai.v24i1.7519"},{"key":"47_CR9","doi-asserted-by":"crossref","unstructured":"Chowdhury, M.F.M., Glass, M.R., Rossiello, G., Gliozzo, A., Mihindukulasooriya, N.: KGI: an integrated framework for knowledge intensive language tasks. CoRR abs\/2204.03985 (2022)","DOI":"10.18653\/v1\/2022.emnlp-demos.28"},{"key":"47_CR10","unstructured":"Dimou, A., Vander Sande, M., Colpaert, P., Verborgh, R., Mannens, E., Van de Walle, R.: RML: a generic language for integrated RDF mappings of heterogeneous data. In: LDOW (2014)"},{"key":"47_CR11","doi-asserted-by":"crossref","unstructured":"Dong, X., et al.: Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In: KDD, pp. 601\u2013610. ACM (2014)","DOI":"10.1145\/2623330.2623623"},{"key":"47_CR12","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/978-1-4899-7637-6_4","volume-title":"Recommender Systems Handbook","author":"M de Gemmis","year":"2015","unstructured":"de Gemmis, M., Lops, P., Musto, C., Narducci, F., Semeraro, G.: Semantics-Aware content-based recommender systems. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 119\u2013159. Springer, Boston, MA (2015). https:\/\/doi.org\/10.1007\/978-1-4899-7637-6_4"},{"key":"47_CR13","doi-asserted-by":"crossref","unstructured":"Glass, M.R., Rossiello, G., Chowdhury, M.F.M., Gliozzo, A.: Robust retrieval augmented generation for zero-shot slot filling. In: EMNLP (1), pp. 1939\u20131949. Association for Computational Linguistics (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.148"},{"key":"47_CR14","doi-asserted-by":"crossref","unstructured":"Heidari, G., Ramadan, A., Stocker, M., Auer, S.: Demonstration of faceted search on scholarly knowledge graphs. In: Companion Proceedings of the Web Conference 2021, pp. 685\u2013686 (2021)","DOI":"10.1145\/3442442.3458605"},{"issue":"2","key":"47_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-01918-0","volume":"12","author":"A Hogan","year":"2021","unstructured":"Hogan, A., et al.: Knowledge graphs. Synth. Lect. Data Semant. Knowl. 12(2), 1\u2013257 (2021)","journal-title":"Synth. Lect. Data Semant. Knowl."},{"key":"47_CR16","doi-asserted-by":"crossref","unstructured":"Jaradeh, M.Y., et al.: Open research knowledge graph: next generation infrastructure for semantic scholarly knowledge. In: Proceedings of the 10th International Conference on Knowledge Capture, pp. 243\u2013246 (2019)","DOI":"10.1145\/3360901.3364435"},{"key":"47_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/978-3-030-54956-5_2","volume-title":"Digital Libraries for Open Knowledge","author":"MY Jaradeh","year":"2020","unstructured":"Jaradeh, M.Y., Stocker, M., Auer, S.: Question answering on scholarly knowledge graphs. In: Hall, M., Mer\u010dun, T., Risse, T., Duchateau, F. (eds.) TPDL 2020. LNCS, vol. 12246, pp. 19\u201332. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-54956-5_2"},{"issue":"2","key":"47_CR18","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1109\/TNNLS.2021.3070843","volume":"33","author":"S Ji","year":"2021","unstructured":"Ji, S., Pan, S., Cambria, E., Marttinen, P., Philip, S.Y.: A survey on knowledge graphs: representation, acquisition, and applications. IEEE Trans. Neural Netw. Learn. Syst. 33(2), 494\u2013514 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"47_CR19","doi-asserted-by":"crossref","unstructured":"Josifoski, M., Cao, N.D., Peyrard, M., West, R.: Genie: generative information extraction. CoRR abs\/2112.08340 (2021)","DOI":"10.18653\/v1\/2022.naacl-main.342"},{"issue":"11","key":"47_CR20","doi-asserted-by":"publisher","first-page":"53","DOI":"10.5815\/ijmecs.2015.11.06","volume":"7","author":"JA Khan","year":"2015","unstructured":"Khan, J.A., Rehman, I.U., Khan, Y.H., Khan, I.J., Rashid, S.: Comparison of requirement prioritization techniques to find best prioritization technique. Int. J. Mod. Educ. Comput. Sci. 7(11), 53\u201359 (2015)","journal-title":"Int. J. Mod. Educ. Comput. Sci."},{"issue":"8","key":"47_CR21","first-page":"4133","volume":"11","author":"Y Kim","year":"2017","unstructured":"Kim, Y., Ju, Y., Hong, S., Jeong, S.R.: Practical text mining for trend analysis: ontology to visualization in aerospace technology. KSII Trans. Internet Inf. Syst. (TIIS) 11(8), 4133\u20134145 (2017)","journal-title":"KSII Trans. Internet Inf. Syst. (TIIS)"},{"key":"47_CR22","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/978-1-4899-7637-6_3","volume-title":"Recommender Systems Handbook","author":"Y Koren","year":"2015","unstructured":"Koren, Y., Bell, R.: Advances in collaborative filtering. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 77\u2013118. Springer, Boston (2015). https:\/\/doi.org\/10.1007\/978-1-4899-7637-6_3"},{"key":"47_CR23","doi-asserted-by":"crossref","unstructured":"Lewis, M., et al.: BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In: ACL, pp. 7871\u20137880. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"47_CR24","doi-asserted-by":"crossref","unstructured":"Liu, J., Duan, L.: A survey on knowledge graph-based recommender systems. In: 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), vol. 5, pp. 2450\u20132453. IEEE (2021)","DOI":"10.1109\/IAEAC50856.2021.9390863"},{"key":"47_CR25","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1007\/978-3-642-35233-1_18","volume-title":"Metadata and Semantics Research","author":"P Manghi","year":"2012","unstructured":"Manghi, P., Houssos, N., Mikulicic, M., J\u00f6rg, B.: The data model of the OpenAIRE scientific communication e-Infrastructure. In: Dodero, J.M., Palomo-Duarte, M., Karampiperis, P. (eds.) MTSR 2012. CCIS, vol. 343, pp. 168\u2013180. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-35233-1_18"},{"key":"47_CR26","unstructured":"Manrique, R., Marino, O.: Knowledge graph-based weighting strategies for a scholarly paper recommendation scenario. In: KaRS@ RecSys, pp. 5\u20138 (2018)"},{"key":"47_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-030-49461-2_15","volume-title":"The Semantic Web","author":"M Nayyeri","year":"2020","unstructured":"Nayyeri, M., Vahdati, S., Zhou, X., Shariat Yazdi, H., Lehmann, J.: Embedding-based recommendations on\u00a0scholarly knowledge graphs. In: Harth, A., et al. (eds.) ESWC 2020. LNCS, vol. 12123, pp. 255\u2013270. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-49461-2_15"},{"key":"47_CR28","unstructured":"Niu, F., Zhang, C., R\u00e9, C., Shavlik, J.W.: DeepDive: web-scale knowledge-base construction using statistical learning and inference. In: VLDS. CEUR Workshop Proceedings, vol. 884, pp. 25\u201328. CEUR-WS.org (2012)"},{"issue":"8","key":"47_CR29","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1145\/3331166","volume":"62","author":"N Noy","year":"2019","unstructured":"Noy, N., Gao, Y., Jain, A., Narayanan, A., Patterson, A., Taylor, J.: Industry-scale knowledge graphs: lessons and challenges. Commun. ACM 62(8), 36\u201343 (2019)","journal-title":"Commun. ACM"},{"key":"47_CR30","doi-asserted-by":"crossref","unstructured":"Oelen, A., Jaradeh, M.Y., Stocker, M., Auer, S.: Generate fair literature surveys with scholarly knowledge graphs. In: Proceedings of the ACM\/IEEE Joint Conference on Digital Libraries in 2020, pp. 97\u2013106 (2020)","DOI":"10.1145\/3383583.3398520"},{"key":"47_CR31","doi-asserted-by":"crossref","unstructured":"Rezayi, S., Zhao, H., Kim, S., Rossi, R., Lipka, N., Li, S.: Edge: enriching knowledge graph embeddings with external text. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), pp. 2767\u20132776 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.221"},{"key":"47_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/978-3-030-88361-4_19","volume-title":"The Semantic Web \u2013 ISWC 2021","author":"G Rossiello","year":"2021","unstructured":"Rossiello, G., et al.: Generative relation linking for question answering over knowledge bases. In: Hotho, A., et al. (eds.) ISWC 2021. LNCS, vol. 12922, pp. 321\u2013337. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88361-4_19"},{"issue":"5","key":"47_CR33","doi-asserted-by":"publisher","first-page":"129","DOI":"10.3390\/fi14050129","volume":"14","author":"V Ryen","year":"2022","unstructured":"Ryen, V., Soylu, A., Roman, D.: Building semantic knowledge graphs from (semi-) structured data: a review. Future Internet 14(5), 129 (2022)","journal-title":"Future Internet"},{"key":"47_CR34","doi-asserted-by":"crossref","unstructured":"de S\u00e1 Mesquita, F., Cannaviccio, M., Schmidek, J., Mirza, P., Barbosa, D.: KnowledgeNet: a benchmark dataset for knowledge base population. In: EMNLP\/IJCNLP (1), pp. 749\u2013758. Association for Computational Linguistics (2019)","DOI":"10.18653\/v1\/D19-1069"},{"key":"47_CR35","unstructured":"Sahoo, S.S., et al.: A survey of current approaches for mapping of relational databases to RDF. W3C RDB2RDF Incubator Group Rep. 1, 113\u2013130 (2009)"},{"key":"47_CR36","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/978-3-030-86668-6_11","volume-title":"Predicting the Dynamics of Research Impact","author":"AA Salatino","year":"2021","unstructured":"Salatino, A.A., Mannocci, A., Osborne, F.: Detection, analysis, and prediction of research topics with scientific knowledge graphs. In: Predicting the Dynamics of Research Impact, pp. 225\u2013252. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86668-6_11"},{"issue":"7837","key":"47_CR37","doi-asserted-by":"publisher","first-page":"S102","DOI":"10.1038\/d41586-020-03409-8","volume":"588","author":"N Savage","year":"2020","unstructured":"Savage, N.: The race to the top among the world\u2019s leaders in artificial intelligence. Nature 588(7837), S102\u2013S102 (2020)","journal-title":"Nature"},{"issue":"10","key":"47_CR38","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/2629489","volume":"57","author":"D Vrande\u010di\u0107","year":"2014","unstructured":"Vrande\u010di\u0107, D., Kr\u00f6tzsch, M.: WikiData: a free collaborative knowledgebase. Commun. ACM 57(10), 78\u201385 (2014)","journal-title":"Commun. ACM"},{"issue":"1","key":"47_CR39","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1162\/qss_a_00021","volume":"1","author":"K Wang","year":"2020","unstructured":"Wang, K., Shen, Z., Huang, C., Wu, C.H., Dong, Y., Kanakia, A.: Microsoft academic graph: when experts are not enough. Quant. Sci. Stud. 1(1), 396\u2013413 (2020)","journal-title":"Quant. Sci. Stud."},{"issue":"1","key":"47_CR40","doi-asserted-by":"publisher","first-page":"39","DOI":"10.4155\/ppa.12.76","volume":"2","author":"L Weber","year":"2013","unstructured":"Weber, L., B\u00f6hme, T., Irmer, M.: Ontology-based content analysis of US patent applications from 2001\u20132010. Pharm. Patent Analyst 2(1), 39\u201354 (2013)","journal-title":"Pharm. Patent Analyst"},{"key":"47_CR41","unstructured":"Wohlgenannt, G., Belk, S., Karacsonyi, M., Schett, M.: Using an ontology learning system for trend analysis and detection. In: International Semantic Web Conference (Posters & Demos), pp. 37\u201340. Citeseer (2014)"}],"container-title":["Lecture Notes in Computer Science","The Semantic Web \u2013 ISWC 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19433-7_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,28]],"date-time":"2023-11-28T23:17:24Z","timestamp":1701213444000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19433-7_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031194320","9783031194337"],"references-count":41,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19433-7_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"16 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISWC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Semantic Web Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"semweb2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iswc2022.semanticweb.org\/","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":"239","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":"48","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":"0","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":"20% - 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":"3.5","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}