{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T21:48:29Z","timestamp":1767649709772,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030006709"},{"type":"electronic","value":"9783030006716"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-030-00671-6_10","type":"book-chapter","created":{"date-parts":[[2018,9,17]],"date-time":"2018-09-17T22:33:02Z","timestamp":1537223582000},"page":"162-178","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Ontology Driven Extraction of Research Processes"],"prefix":"10.1007","author":[{"given":"Vayianos","family":"Pertsas","sequence":"first","affiliation":[]},{"given":"Panos","family":"Constantopoulos","sequence":"additional","affiliation":[]},{"given":"Ion","family":"Androutsopoulos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,18]]},"reference":[{"key":"10_CR1","doi-asserted-by":"publisher","first-page":"2215","DOI":"10.1002\/asi.23329","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. J. Assoc. Inf. Sci. Technol. Technol. 66, 2215\u20132222 (2015)","journal-title":"J. Assoc. Inf. Sci. Technol. Technol."},{"key":"10_CR2","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1126\/science.1157784","volume":"325","author":"AH Renear","year":"2009","unstructured":"Renear, A.H., Palmer, C.L.: Strategic reading, ontologies, and the future of scientific publishing. Science 325, 828\u2013832 (2009)","journal-title":"Science"},{"key":"10_CR3","unstructured":"Augenstein, I., Das, M., Riedel, S., Vikraman, L., McCallum, A.: SemEval 2017 Task 10: ScienceIE, pp. 546\u2013555 (2017)"},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s00799-016-0169-3","volume":"18","author":"V Pertsas","year":"2017","unstructured":"Pertsas, V., Constantopoulos, P.: Scholarly ontology: modelling scholarly practices. Int. J. Digit. Libraries. 18, 173\u2013190 (2017)","journal-title":"Int. J. Digit. Libraries."},{"key":"10_CR5","doi-asserted-by":"crossref","unstructured":"Levy, O., Goldberg, Y.: Linguistic regularities in sparse and explicit word representations. In: CoNLL, pp. 171\u2013180 (2014)","DOI":"10.3115\/v1\/W14-1618"},{"key":"10_CR6","first-page":"211","volume":"3","author":"O Levy","year":"2015","unstructured":"Levy, O., Goldberg, Y., Dagan, I.: Improving distributional similarity with lessons learned from word embeddings. Trans. ACL 3, 211\u2013225 (2015)","journal-title":"Trans. ACL"},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"Chalkidis, I., Michos, A., Androutsopoulos, I.: Extracting contract elements. In: ICAIL, pp. 19\u201328, London (2017)","DOI":"10.1145\/3086512.3086515"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"McCullagh, P., Nelder, J.A.: Generalized Linear Models, Chapman and Hall London \u2013 New York (1983). 261 S","DOI":"10.1007\/978-1-4899-3244-0"},{"key":"10_CR9","isbn-type":"print","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511801389","volume-title":"An introduction to support vector machines and other kernel-based learning methods","author":"N Cristianini","year":"2000","unstructured":"Cristianini, N., Shawe-Taylor, J.: An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge (2000). ISBN 0-521-78019-5","ISBN":"https:\/\/id.crossref.org\/isbn\/0521780195"},{"key":"10_CR10","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"10_CR11","unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.N.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: ICML 2001. vol. 8, pp. 282\u2013289 (2001)"},{"key":"10_CR12","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1613\/jair.4992","volume":"57","author":"Y Goldberg","year":"2016","unstructured":"Goldberg, Y.: A primer on neural network models for natural language processing. J. Artif. Intell. Res. 57, 345\u2013420 (2016)","journal-title":"J. Artif. Intell. Res."},{"key":"10_CR13","unstructured":"QasemiZadeh, B., Schumann, A.-K.: The ACL RD-TEC 2.0: a language resource for evaluating term extraction and entity recognition methods. In: LREC, pp. 1862\u20131868 (2016)"},{"key":"10_CR14","doi-asserted-by":"crossref","unstructured":"Lee, L.-H., Lee, K.-C., Tseng, Y.-H.: The NTNU System at SemEval-2017 Task 10: extracting keyphrases and relations from scientific publications using multiple CRFs. In: 11th International Workshop on SemEval-2017, pp. 950\u2013954 (2017)","DOI":"10.18653\/v1\/S17-2165"},{"key":"10_CR15","doi-asserted-by":"crossref","unstructured":"Luan, Y., Ostendorf, M., Hajishirzi, H.: Scientific Information Extraction with Semi-supervised Neural Tagging, pp. 2631\u20132641. arXiv:1708.06075 (2017)","DOI":"10.18653\/v1\/D17-1279"},{"key":"10_CR16","doi-asserted-by":"publisher","unstructured":"Sateli, B., Witte, R.: What\u2019s in this paper? Combining rhetorical entities with linked open data for semantic literature querying. In: ICWWW ACM, pp. 1023\u20131028 (2015). https:\/\/doi.org\/10.1145\/2740908.2742022","DOI":"10.1145\/2740908.2742022"},{"key":"10_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1007\/978-3-319-49004-5_30","volume-title":"Knowledge Engineering and Knowledge Management","author":"F Osborne","year":"2016","unstructured":"Osborne, F., de Ribaupierre, H., Motta, E.: TechMiner: extracting technologies from academic publications. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds.) EKAW 2016. LNCS (LNAI), vol. 10024, pp. 463\u2013479. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49004-5_30"},{"key":"10_CR18","doi-asserted-by":"publisher","first-page":"e37","DOI":"10.7717\/peerj-cs.37","volume":"1","author":"B Sateli","year":"2015","unstructured":"Sateli, B., Witte, R.: Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud. PeerJ Comput. Sci. 1, e37 (2015)","journal-title":"PeerJ Comput. Sci."},{"key":"10_CR19","unstructured":"Song, Y., Yi, E., Kim, E., Lee, G.G., Park, S.J.: POSBIOTM-NER: a machine learning approach for bio-named entity recognition (2004). Doi=10.1.1.101.1165"},{"key":"10_CR20","unstructured":"Plake, C., et al.: A support vector classifier for gene name recognition. In: BioCreAtIvE Workshop, Granada, Spain, pp. 1\u20135 (2004)"},{"key":"10_CR21","unstructured":"Gupta, S., Manning, C.: Analyzing the dynamics of research by extracting key aspects of scientific papers. In: IJCNLP, pp. 1\u20139 (2011)"},{"key":"10_CR22","doi-asserted-by":"publisher","first-page":"e119","DOI":"10.7717\/peerj-cs.119","volume":"3","author":"AA Salatino","year":"2017","unstructured":"Salatino, A.A., Osborne, F., Motta, E.: How are topics born? Understanding the research dynamics preceding the emergence of new areas. PeerJ Comput. Sci. 3, e119 (2017)","journal-title":"PeerJ Comput. Sci."},{"key":"10_CR23","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.ijmedinf.2006.05.002","volume":"76","author":"P Ruch","year":"2007","unstructured":"Ruch, P., et al.: Using argumentation to extract key sentences from biomedical abstracts. Int. J. Med. Inform. 76, 195\u2013200 (2007)","journal-title":"Int. J. Med. Inform."},{"key":"10_CR24","unstructured":"Di Iorio, A., Nuzzolese, A.G., Peroni, S.: Towards the automatic identification of the nature of citations. In: CEUR Workshop Proceedings, pp. 63\u201374 (2013)"},{"key":"10_CR25","unstructured":"Athar, A., Teufel, S.: Context-enhanced citation sentiment detection. In: NAACL HLT 2012, pp. 597\u2013601 (2012)"},{"key":"10_CR26","doi-asserted-by":"crossref","unstructured":"Do, H.H.N., Chandrasekaran, M.K., Cho, P.S., Kan, M.-Y.: Extracting and matching authors and affiliations in scholarly documents. In: ACM\/IEEE-CS - JCDL 2013, pp. 219\u2013228 (2013)","DOI":"10.1145\/2467696.2467703"},{"key":"10_CR27","doi-asserted-by":"crossref","unstructured":"Lindsay, A., Read, J., Ferreira, J.F., Hayton, T., Porteous, J., Gregory, P.: Framer: planning models from natural language action descriptions. In: ICAPS, pp. 434\u2013442 (2017)","DOI":"10.1609\/icaps.v27i1.13850"},{"key":"10_CR28","doi-asserted-by":"crossref","unstructured":"Feng, W., Zhuo, H.H., Kambhampati, S.: Extracting Action Sequences from Texts Based on Deep Reinforcement Learning. arXiv:1803.02632 (2018)","DOI":"10.24963\/ijcai.2018\/565"},{"key":"10_CR29","doi-asserted-by":"crossref","unstructured":"Mei, H., Bansal, M., Walter, M.R.: Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences. arXiv:1506.04089 (2015)","DOI":"10.1609\/aaai.v30i1.10364"},{"key":"10_CR30","unstructured":"Pertsas, V., Christodoulou, T., Dallas, C., Constantopoulos, P., Papachristopoulos, L., Hughes, L.: Contextualized integration of digital humanities research: using the NeMO ontology of digital humanities methods. In: Digital Humanities 2016: Conference Abstracts, pp. 161\u2013163. Jagiellonian University & Pedagogical University (2016)"},{"key":"10_CR31","doi-asserted-by":"crossref","unstructured":"Yeh, A.: More accurate tests for the statistical significance of result differences. In: COLING. vol. 2, pp. 947\u2013953 (2000)","DOI":"10.3115\/992730.992783"}],"container-title":["Lecture Notes in Computer Science","The Semantic Web \u2013 ISWC 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00671-6_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T17:46:23Z","timestamp":1709833583000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00671-6_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030006709","9783030006716"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00671-6_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"18 September 2018","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":"Monterey, CA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"semweb2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iswc2018.semanticweb.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}