{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T16:52:20Z","timestamp":1771606340776,"version":"3.50.1"},"reference-count":109,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:00:00Z","timestamp":1671062400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:00:00Z","timestamp":1671062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100014736","name":"Lingnan University","doi-asserted-by":"publisher","award":["Direct Grant (DR22A2)"],"award-info":[{"award-number":["Direct Grant (DR22A2)"]}],"id":[{"id":"10.13039\/501100014736","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014736","name":"Lingnan University","doi-asserted-by":"publisher","award":["the Faculty Research Grants (DB22B4"],"award-info":[{"award-number":["the Faculty Research Grants (DB22B4"]}],"id":[{"id":"10.13039\/501100014736","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014736","name":"Lingnan University","doi-asserted-by":"publisher","award":["DB22B7)"],"award-info":[{"award-number":["DB22B7)"]}],"id":[{"id":"10.13039\/501100014736","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Education University of Hong Kong","award":["the One-off Special Fund from Central"],"award-info":[{"award-number":["the One-off Special Fund from Central"]}]},{"name":"The Education University of Hong Kong","award":["Faculty Fund in Support of Research from 2019\/20 to 2021\/22 (MIT02\/19-20)"],"award-info":[{"award-number":["Faculty Fund in Support of Research from 2019\/20 to 2021\/22 (MIT02\/19-20)"]}]},{"name":"The Education University of Hong Kong","award":["Interdisciplinary Research Scheme of Dean\u2019s Research Fund 2021\/22 (FLASS\/DRF\/IDS-3)"],"award-info":[{"award-number":["Interdisciplinary Research Scheme of Dean\u2019s Research Fund 2021\/22 (FLASS\/DRF\/IDS-3)"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s13042-022-01710-8","type":"journal-article","created":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T02:02:31Z","timestamp":1671069751000},"page":"1483-1525","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Leveraging deep learning for automatic literature screening in intelligent bibliometrics"],"prefix":"10.1007","volume":"14","author":[{"given":"Xieling","family":"Chen","sequence":"first","affiliation":[]},{"given":"Haoran","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Zongxi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Dian","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Gary","family":"Cheng","sequence":"additional","affiliation":[]},{"given":"Fu Lee","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Hong-Ning","family":"Dai","sequence":"additional","affiliation":[]},{"given":"Qing","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,15]]},"reference":[{"key":"1710_CR1","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1007\/s11920-019-1094-0","volume":"21","author":"S Graham","year":"2019","unstructured":"Graham S, Depp C, Lee EE et al (2019) Artificial intelligence for mental health and mental illnesses: an overview. Curr Psychiatry Rep 21:116","journal-title":"Curr Psychiatry Rep"},{"key":"1710_CR2","doi-asserted-by":"crossref","first-page":"2157","DOI":"10.3390\/app10062157","volume":"10","author":"X Chen","year":"2020","unstructured":"Chen X, Xie H, Cheng G et al (2020) Trends and features of the applications of natural language processing techniques for clinical trials text analysis. Appl Sci 10:2157","journal-title":"Appl Sci"},{"key":"1710_CR3","doi-asserted-by":"crossref","first-page":"3575","DOI":"10.1007\/s13042-019-00945-2","volume":"10","author":"N Balakrishnan","year":"2019","unstructured":"Balakrishnan N, Rajendran A, Palanivel K (2019) Meticulous fuzzy convolution C means for optimized big data analytics: adaptation towards deep learning. Int J Mach Learn Cybern 10:3575\u20133586","journal-title":"Int J Mach Learn Cybern"},{"key":"1710_CR4","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1108\/01409170410784185","volume":"27","author":"J Rowley","year":"2004","unstructured":"Rowley J, Slack F (2004) Conducting a literature review. Manag Res news 27:31\u201339","journal-title":"Manag Res news"},{"key":"1710_CR5","volume-title":"Reviewing and the research imagination: doing a literature review","author":"C Hart","year":"1998","unstructured":"Hart C (1998) Reviewing and the research imagination: doing a literature review. Sage, London"},{"key":"1710_CR6","unstructured":"Webster J, Watson RT (2002) Analyzing the past to prepare for the future: Writing a literature review. MIS Q xiii\u2013xxiii"},{"key":"1710_CR7","doi-asserted-by":"crossref","first-page":"38","DOI":"10.12968\/bjon.2008.17.1.28059","volume":"17","author":"P Cronin","year":"2008","unstructured":"Cronin P, Ryan F, Coughlan M (2008) Undertaking a literature review: a step-by-step approach. Br J Nurs 17:38\u201343","journal-title":"Br J Nurs"},{"key":"1710_CR8","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1162\/qss_a_00100","volume":"2","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Wu M, Hu Z et al (2021) Profiling and predicting the problem-solving patterns in china\u2019s research systems: a methodology of intelligent bibliometrics and empirical insights. Quant Sci Stud 2:409\u2013432","journal-title":"Quant Sci Stud"},{"key":"1710_CR9","first-page":"9","volume":"37","author":"J Vom Brocke","year":"2015","unstructured":"Vom Brocke J, Simons A, Riemer K et al (2015) Standing on the shoulders of giants: challenges and recommendations of literature search in information systems research. Commun Assoc Inf Syst 37:9","journal-title":"Commun Assoc Inf Syst"},{"key":"1710_CR10","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.1002\/asi.22688","volume":"63","author":"MJ Cobo","year":"2012","unstructured":"Cobo MJ, L\u00f3pez-Herrera AG, Herrera-Viedma E, Herrera F (2012) SciMAT: a new science mapping analysis software tool. J Am Soc Inf Sci Technol 63:1609\u20131630","journal-title":"J Am Soc Inf Sci Technol"},{"key":"1710_CR11","unstructured":"\u00c5str\u00f6m F, Danell R, Larsen B, Schneider J (2009) Celebrating scholarly communication studies: A Festschrift for Olle Persson at his 60th Birthday. ISSI"},{"key":"1710_CR12","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/s11192-009-0146-3","volume":"84","author":"N Van Eck","year":"2010","unstructured":"Van Eck N, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84:523\u2013538","journal-title":"Scientometrics"},{"key":"1710_CR13","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1002\/asi.20317","volume":"57","author":"C Chen","year":"2006","unstructured":"Chen C (2006) CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci Technol 57:359\u2013377","journal-title":"J Am Soc Inf Sci Technol"},{"key":"1710_CR14","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1016\/j.joi.2014.07.006","volume":"8","author":"NJ Van Eck","year":"2014","unstructured":"Van Eck NJ, Waltman L (2014) CitNetExplorer: a new software tool for analyzing and visualizing citation networks. J Informetr 8:802\u2013823","journal-title":"J Informetr"},{"key":"1710_CR15","unstructured":"Team S (2009) Sci2 Tool: A Tool for Science of Science Research and Practice. https:\/\/sci2.cns.iu.edu."},{"key":"1710_CR16","doi-asserted-by":"crossref","unstructured":"Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. In: Proceedings of the International AAAI Conference on Web and Social Media (Volume 3), pp 361\u2013362. Retrieved from https:\/\/ojs.aaai.org\/index.php\/ICWSM\/article\/view\/13937","DOI":"10.1609\/icwsm.v3i1.13937"},{"key":"1710_CR17","doi-asserted-by":"crossref","first-page":"943","DOI":"10.1007\/s11192-011-0482-y","volume":"89","author":"S Grauwin","year":"2011","unstructured":"Grauwin S, Jensen P (2011) Mapping scientific institutions. Scientometrics 89:943\u2013954","journal-title":"Scientometrics"},{"key":"1710_CR18","doi-asserted-by":"crossref","first-page":"2766","DOI":"10.1002\/asi.23605","volume":"67","author":"CW Belter","year":"2016","unstructured":"Belter CW (2016) Citation analysis as a literature search method for systematic reviews. J Assoc Inf Sci Technol 67:2766\u20132777","journal-title":"J Assoc Inf Sci Technol"},{"key":"1710_CR19","doi-asserted-by":"crossref","unstructured":"Hearst MA (1999) Untangling text data mining. In: Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics. Association for Computational Linguistics, pp 3\u201310","DOI":"10.3115\/1034678.1034679"},{"key":"1710_CR20","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1109\/TPAMI.1980.4767011","volume":"2","author":"S Raudys","year":"1980","unstructured":"Raudys S, Pikelis V (1980) On dimensionality, sample size, classification error, and complexity of classification algorithm in pattern recognition. IEEE Trans Pattern Anal Mach Intell 2:242\u2013252","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1710_CR21","doi-asserted-by":"crossref","first-page":"3209","DOI":"10.3390\/app12063209","volume":"12","author":"A Taha","year":"2022","unstructured":"Taha A, Cosgrave B, Mckeever S (2022) Using feature selection with machine learning for generation of insurance insights. Appl Sci 12:3209","journal-title":"Appl Sci"},{"key":"1710_CR22","unstructured":"Langley P, Iba W (1993) Average-case analysis of a nearest neighbor algorithm. In: IJCAI. Citeseer, p 889"},{"key":"1710_CR23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s42452-021-04148-9","volume":"3","author":"M Saarela","year":"2021","unstructured":"Saarela M, Jauhiainen S (2021) Comparison of feature importance measures as explanations for classification models. SN Appl Sci 3:1\u201312","journal-title":"SN Appl Sci"},{"key":"1710_CR24","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1016\/j.eswa.2012.09.017","volume":"40","author":"O Kwon","year":"2013","unstructured":"Kwon O, Sim JM (2013) Effects of data set features on the performances of classification algorithms. Expert Syst Appl 40:1847\u20131857","journal-title":"Expert Syst Appl"},{"key":"1710_CR25","first-page":"1157","volume":"3","author":"I Guyon","year":"2003","unstructured":"Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157\u20131182","journal-title":"J Mach Learn Res"},{"key":"1710_CR26","doi-asserted-by":"crossref","first-page":"2906","DOI":"10.1016\/j.asoc.2010.11.028","volume":"11","author":"Y Peng","year":"2011","unstructured":"Peng Y, Wang G, Kou G, Shi Y (2011) An empirical study of classification algorithm evaluation for financial risk prediction. Appl Soft Comput 11:2906\u20132915","journal-title":"Appl Soft Comput"},{"key":"1710_CR27","doi-asserted-by":"crossref","first-page":"796","DOI":"10.3390\/app11020796","volume":"11","author":"A Althnian","year":"2021","unstructured":"Althnian A, AlSaeed D, Al-Baity H et al (2021) Impact of dataset size on classification performance: an empirical evaluation in the medical domain. Appl Sci 11:796","journal-title":"Appl Sci"},{"key":"1710_CR28","doi-asserted-by":"crossref","unstructured":"Prusa J, Khoshgoftaar TM, Seliya N (2015) The effect of dataset size on training tweet sentiment classifiers. In: 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA). IEEE, pp 96\u2013102","DOI":"10.1109\/ICMLA.2015.22"},{"key":"1710_CR29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12874-016-0277-1","volume":"17","author":"MS Rahman","year":"2017","unstructured":"Rahman MS, Sultana M (2017) Performance of Firth-and logF-type penalized methods in risk prediction for small or sparse binary data. BMC Med Res Methodol 17:1\u201315","journal-title":"BMC Med Res Methodol"},{"key":"1710_CR30","volume-title":"Balancing the strengths of systematic and narrative reviews","author":"JA Collins","year":"2005","unstructured":"Collins JA, Fauser BCJM (2005) Balancing the strengths of systematic and narrative reviews. Oxford University Press, Oxford"},{"key":"1710_CR31","unstructured":"Boell SK, Cecez-Kecmanovic D On Being \u2018Systematic\u2019in Literature Reviews in IS. In Formulating Research Methods for Information Systems. Springer, pp 8\u201378"},{"key":"1710_CR32","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1590\/S0104-42302004000100045","volume":"50","author":"WM Bernardo","year":"2004","unstructured":"Bernardo WM, Nobre MRC, Jatene FB (2004) Evidence based clinical practice: part II-searching evidence databases. Rev Assoc Med Bras 50:104\u2013108","journal-title":"Rev Assoc Med Bras"},{"key":"1710_CR33","volume-title":"Nursing research: principles, process and issues","author":"K Parahoo","year":"2006","unstructured":"Parahoo K (2006) Nursing research: principles, process and issues. Bloomsbury Publishing, London"},{"key":"1710_CR34","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.compedu.2019.04.004","volume":"137","author":"TJ Dunn","year":"2019","unstructured":"Dunn TJ, Kennedy M (2019) Technology enhanced learning in higher education; motivations, engagement and academic achievement. Comput Educ 137:104\u2013113","journal-title":"Comput Educ"},{"key":"1710_CR35","volume":"140","author":"H Xie","year":"2019","unstructured":"Xie H, Chu H-C, Hwang G-J, Wang C-C (2019) Trends and development in technology-enhanced adaptive\/personalized learning: a systematic review of journal publications from 2007 to 2017. Comput Educ 140:103599","journal-title":"Comput Educ"},{"key":"1710_CR36","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1002\/smj.397","volume":"25","author":"A Ramos-Rodr\u00edguez","year":"2004","unstructured":"Ramos-Rodr\u00edguez A, Ru\u00edz-Navarro J (2004) Changes in the intellectual structure of strategic management research: a bibliometric study of the Strategic Management Journal, 1980\u20132000. Strateg Manag J 25:981\u20131004","journal-title":"Strateg Manag J"},{"key":"1710_CR37","doi-asserted-by":"crossref","first-page":"391","DOI":"10.3390\/su10020391","volume":"10","author":"E Gimenez","year":"2018","unstructured":"Gimenez E, Salinas M, Manzano-Agugliaro F (2018) Worldwide research on plant defense against biotic stresses as improvement for sustainable agriculture. Sustainability 10:391","journal-title":"Sustainability"},{"key":"1710_CR38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12911-017-0580-8","volume":"18","author":"X Chen","year":"2018","unstructured":"Chen X, Xie H, Wang FL et al (2018) A bibliometric analysis of natural language processing in medical research. BMC Med Inform Decis Mak 18:1\u201314","journal-title":"BMC Med Inform Decis Mak"},{"key":"1710_CR39","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.compedu.2019.04.002","volume":"137","author":"Y Song","year":"2019","unstructured":"Song Y, Chen X, Hao T et al (2019) Exploring two decades of research on classroom dialogue by using bibliometric analysis. Comput Educ 137:12\u201331","journal-title":"Comput Educ"},{"key":"1710_CR40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13643-016-0263-z","volume":"5","author":"BE Howard","year":"2016","unstructured":"Howard BE, Phillips J, Miller K et al (2016) SWIFT-Review: a text-mining workbench for systematic review. Syst Rev 5:1\u201316","journal-title":"Syst Rev"},{"key":"1710_CR41","doi-asserted-by":"crossref","unstructured":"Scells H, Zuccon G, Koopman B, et al (2017) A test collection for evaluating retrieval of studies for inclusion in systematic reviews. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. pp 1237\u20131240","DOI":"10.1145\/3077136.3080707"},{"key":"1710_CR42","doi-asserted-by":"crossref","first-page":"224","DOI":"10.7326\/0003-4819-147-4-200708210-00179","volume":"147","author":"KG Shojania","year":"2007","unstructured":"Shojania KG, Sampson M, Ansari MT et al (2007) How quickly do systematic reviews go out of date? A survival analysis. Ann Intern Med 147:224\u2013233","journal-title":"Ann Intern Med"},{"key":"1710_CR43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13643-021-01881-5","volume":"11","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Liang S, Feng Y et al (2022) Automation of literature screening using machine learning in medical evidence synthesis: a diagnostic test accuracy systematic review protocol. Syst Rev 11:1\u20137","journal-title":"Syst Rev"},{"key":"1710_CR44","volume":"11","author":"S Lee","year":"2016","unstructured":"Lee S, Kim D, Lee K et al (2016) BEST: next-generation biomedical entity search tool for knowledge discovery from biomedical literature. PLoS ONE 11:e0164680","journal-title":"PLoS ONE"},{"key":"1710_CR45","volume-title":"Systematic reviews in the social sciences: a practical guide","author":"M Petticrew","year":"2008","unstructured":"Petticrew M, Roberts H (2008) Systematic reviews in the social sciences: a practical guide. John Wiley & Sons, New York"},{"key":"1710_CR46","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1016\/j.jclinepi.2012.03.009","volume":"65","author":"ME Kho","year":"2012","unstructured":"Kho ME, Brouwers MC (2012) The systematic review and bibliometric network analysis (SeBriNA) is a new method to contextualize evidence. Part 1: description. J Clin Epidemiol 65:1010\u20131015","journal-title":"J Clin Epidemiol"},{"key":"1710_CR47","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1016\/j.jclinepi.2013.11.015","volume":"67","author":"KA Robinson","year":"2014","unstructured":"Robinson KA, Dunn AG, Tsafnat G, Glasziou P (2014) Citation networks of related trials are often disconnected: implications for bidirectional citation searches. J Clin Epidemiol 67:793\u2013799","journal-title":"J Clin Epidemiol"},{"key":"1710_CR48","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1197\/jamia.M1909","volume":"13","author":"EV Bernstam","year":"2006","unstructured":"Bernstam EV, Herskovic JR, Aphinyanaphongs Y et al (2006) Using citation data to improve retrieval from MEDLINE. J Am Med Informatics Assoc 13:96\u2013105","journal-title":"J Am Med Informatics Assoc"},{"key":"1710_CR49","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1186\/2046-4053-3-125","volume":"3","author":"F Bunn","year":"2014","unstructured":"Bunn F, Trivedi D, Alderson P et al (2014) The impact of Cochrane systematic reviews: a mixed method evaluation of outputs from Cochrane Review Groups supported by the UK National Institute for Health Research. Syst Rev 3:125","journal-title":"Syst Rev"},{"key":"1710_CR50","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1186\/2046-4053-2-74","volume":"2","author":"P Royle","year":"2013","unstructured":"Royle P, Kandala N-B, Barnard K, Waugh N (2013) Bibliometrics of systematic reviews: analysis of citation rates and journal impact factors. Syst Rev 2:74","journal-title":"Syst Rev"},{"key":"1710_CR51","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1002\/jrsm.1094","volume":"5","author":"A O\u2019Mara-Eves","year":"2014","unstructured":"O\u2019Mara-Eves A, Brunton G, McDaid D et al (2014) Techniques for identifying cross-disciplinary and \u2018hard-to-detect\u2019evidence for systematic review. Res Synth Methods 5:50\u201359","journal-title":"Res Synth Methods"},{"key":"1710_CR52","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1002\/jrsm.1093","volume":"5","author":"I Shemilt","year":"2014","unstructured":"Shemilt I, Simon A, Hollands GJ et al (2014) Pinpointing needles in giant haystacks: use of text mining to reduce impractical screening workload in extremely large scoping reviews. Res Synth Methods 5:31\u201349","journal-title":"Res Synth Methods"},{"key":"1710_CR53","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1016\/j.eswa.2013.08.047","volume":"41","author":"JJG Adeva","year":"2014","unstructured":"Adeva JJG, Atxa JMP, Carrillo MU, Zengotitabengoa EA (2014) Automatic text classification to support systematic reviews in medicine. Expert Syst Appl 41:1498\u20131508","journal-title":"Expert Syst Appl"},{"key":"1710_CR54","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.eswa.2018.11.021","volume":"120","author":"Z Yu","year":"2019","unstructured":"Yu Z, Menzies T (2019) FAST2: an intelligent assistant for finding relevant papers. Expert Syst Appl 120:57\u201371","journal-title":"Expert Syst Appl"},{"key":"1710_CR55","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.115261","volume":"182","author":"R van Dinter","year":"2021","unstructured":"van Dinter R, Catal C, Tekinerdogan B (2021) A decision support system for automating document retrieval and citation screening. Expert Syst Appl 182:115261","journal-title":"Expert Syst Appl"},{"key":"1710_CR56","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbi.2020.103539","volume":"110","author":"C Col\u00f3n-Ruiz","year":"2020","unstructured":"Col\u00f3n-Ruiz C, Segura-Bedmar I (2020) Comparing deep learning architectures for sentiment analysis on drug reviews. J Biomed Inform 110:103539","journal-title":"J Biomed Inform"},{"key":"1710_CR57","volume":"6","author":"G Kontonatsios","year":"2020","unstructured":"Kontonatsios G, Spencer S, Matthew P, Korkontzelos I (2020) Using a neural network-based feature extraction method to facilitate citation screening for systematic reviews. Expert Syst with Appl X 6:100030","journal-title":"Expert Syst with Appl X"},{"key":"1710_CR58","doi-asserted-by":"crossref","unstructured":"Ros R, Bjarnason E, Runeson P (2017) A machine learning approach for semi-automated search and selection in literature studies. In: Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering. pp 118\u2013127","DOI":"10.1145\/3084226.3084243"},{"key":"1710_CR59","doi-asserted-by":"crossref","DOI":"10.1016\/j.infsof.2020.106395","volume":"128","author":"WM Watanabe","year":"2020","unstructured":"Watanabe WM, Felizardo KR, Candido A Jr et al (2020) Reducing efforts of software engineering systematic literature reviews updates using text classification. Inf Softw Technol 128:106395","journal-title":"Inf Softw Technol"},{"key":"1710_CR60","doi-asserted-by":"crossref","first-page":"835","DOI":"10.3389\/fphys.2018.00835","volume":"9","author":"Z Xiong","year":"2018","unstructured":"Xiong Z, Liu T, Tse G et al (2018) A machine learning aided systematic review and meta-analysis of the relative risk of atrial fibrillation in patients with diabetes mellitus. Front Physiol 9:835","journal-title":"Front Physiol"},{"key":"1710_CR61","doi-asserted-by":"crossref","unstructured":"Timsina P, Liu J, El-Gayar O, Shang Y (2016) Using semi-supervised learning for the creation of medical systematic review: An exploratory analysis. In: 2016 49th Hawaii International Conference on System Sciences (HICSS). IEEE, pp 1195\u20131203","DOI":"10.1109\/HICSS.2016.151"},{"key":"1710_CR62","doi-asserted-by":"crossref","first-page":"3161","DOI":"10.1007\/s10664-017-9587-0","volume":"23","author":"Z Yu","year":"2018","unstructured":"Yu Z, Kraft NA, Menzies T (2018) Finding better active learners for faster literature reviews. Empir Softw Eng 23:3161\u20133186","journal-title":"Empir Softw Eng"},{"key":"1710_CR63","doi-asserted-by":"crossref","unstructured":"Wang D, Weisz JD, Muller M, et al (2019) Human-AI collaboration in data science: Exploring data scientists\u2019 perceptions of automated AI. Proc ACM Human-Computer Interact, pp 1\u201314.","DOI":"10.1145\/3359313"},{"key":"1710_CR64","first-page":"431","volume":"30","author":"A Oussous","year":"2018","unstructured":"Oussous A, Benjelloun FZ, Ait Lahcen A, Belfkih S (2018) Big Data technologies: a survey. J King Saud Univ Comput Inf Sci 30:431\u2013448","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"1710_CR65","volume":"108","author":"B Kim","year":"2021","unstructured":"Kim B, Yoo M, Park KC et al (2021) A value of civic voices for smart city: a big data analysis of civic queries posed by Seoul citizens. Cities 108:102941","journal-title":"Cities"},{"key":"1710_CR66","doi-asserted-by":"crossref","first-page":"1262","DOI":"10.1016\/j.tele.2017.05.011","volume":"34","author":"T Ha","year":"2017","unstructured":"Ha T, Beijnon B, Kim S et al (2017) Examining user perceptions of smartwatch through dynamic topic modeling. Telemat Informat 34:1262\u20131273","journal-title":"Telemat Informat"},{"key":"1710_CR67","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.techfore.2017.01.011","volume":"117","author":"GA Barnett","year":"2017","unstructured":"Barnett GA, Ruiz JB, Xu WW et al (2017) The world is not flat: evaluating the inequality in global information gatekeeping through website co-mentions. Technol Forecast Soc Change 117:38\u201345","journal-title":"Technol Forecast Soc Change"},{"key":"1710_CR68","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1177\/1461444815604421","volume":"19","author":"GA Barnett","year":"2017","unstructured":"Barnett GA, Benefield GA (2017) Predicting international Facebook ties through cultural homophily and other factors. New Media Soc 19:217\u2013239","journal-title":"New Media Soc"},{"key":"1710_CR69","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1108\/JCEFTS-05-2017-0013","volume":"10","author":"S Cheah","year":"2017","unstructured":"Cheah S, Wang S (2017) Big data-driven business model innovation by traditional industries in the Chinese economy. J Chinese Econ Foreign Trade Stud 10:229\u2013251","journal-title":"J Chinese Econ Foreign Trade Stud"},{"key":"1710_CR70","doi-asserted-by":"crossref","unstructured":"Lewis DD (1998) Naive (Bayes) at forty: The independence assumption in information retrieval. In: European conference on machine learning. Springer, pp 4\u201315","DOI":"10.1007\/BFb0026666"},{"key":"1710_CR71","unstructured":"McCallum A, Nigam K (1998) A comparison of event models for naive bayes text classification. In: AAAI-98 workshop on learning for text categorization. Citeseer, pp 41\u201348"},{"key":"1710_CR72","first-page":"420","volume-title":"European Conference on Information Retrieval","author":"A Moschitti","year":"2003","unstructured":"Moschitti A (2003) A study on optimal parameter tuning for Rocchio text classifier. In: Sebastiani F (ed) European Conference on Information Retrieval. Springer, Berlin, pp 420\u2013435"},{"key":"1710_CR73","doi-asserted-by":"crossref","unstructured":"Jabbar MA, Deekshatulu BL, Chndra P (2014) Alternating decision trees for early diagnosis of heart disease. In: International Conference on Circuits, Communication, Control and Computing. IEEE, pp 322\u2013328","DOI":"10.1109\/CIMCA.2014.7057816"},{"key":"1710_CR74","first-page":"272","volume":"9","author":"J Ali","year":"2012","unstructured":"Ali J, Khan R, Ahmad N, Maqsood I (2012) Random forests and decision trees. Int J Comput Sci Issues 9:272","journal-title":"Int J Comput Sci Issues"},{"key":"1710_CR75","first-page":"602","volume":"2","author":"K Fawagreh","year":"2014","unstructured":"Fawagreh K, Gaber MM, Elyan E (2014) Random forests: from early developments to recent advancements. Syst Sci Control Eng An Open Access J 2:602\u2013609","journal-title":"Syst Sci Control Eng An Open Access J"},{"key":"1710_CR76","volume-title":"Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment","author":"K Roy","year":"2015","unstructured":"Roy K, Kar S, Das RN (2015) Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment. Academic press, Cambridge"},{"key":"1710_CR77","unstructured":"Socher R, Pennington J, Huang EH, et al (2011) Semi-supervised recursive autoencoders for predicting sentiment distributions. In: Proceedings of the conference on empirical methods in natural language processing. Association for Computational Linguistics, pp 151\u2013161"},{"key":"1710_CR78","doi-asserted-by":"crossref","unstructured":"Iyyer M, Enns P, Boyd-Graber J, Resnik P (2014) Political ideology detection using recursive neural networks. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp 1113\u20131122","DOI":"10.3115\/v1\/P14-1105"},{"key":"1710_CR79","doi-asserted-by":"crossref","unstructured":"Kim Y (2014) Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp 1746\u20131751","DOI":"10.3115\/v1\/D14-1181"},{"key":"1710_CR80","unstructured":"Mikolov T, Grave E, Bojanowski P, et al (2017) Advances in pre-training distributed word representations. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). Retrieved from https:\/\/arxiv.org\/pdf\/1712.09405.pdf"},{"key":"1710_CR81","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13244-021-01052-z","volume":"12","author":"LL Iglesias","year":"2021","unstructured":"Iglesias LL, Bell\u00f3n PS, del Barrio AP et al (2021) A primer on deep learning and convolutional neural networks for clinicians. Insights Imaging 12:1\u201311","journal-title":"Insights Imaging"},{"key":"1710_CR82","doi-asserted-by":"crossref","unstructured":"Yih W, He X, Meek C (2014) Semantic parsing for single-relation question answering. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp 643\u2013648","DOI":"10.3115\/v1\/P14-2105"},{"key":"1710_CR83","doi-asserted-by":"crossref","unstructured":"Kalchbrenner N, Grefenstette E, Blunsom P (2014) A convolutional neural network for modelling sentences. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp 655\u2013665.","DOI":"10.3115\/v1\/P14-1062"},{"key":"1710_CR84","doi-asserted-by":"crossref","unstructured":"Shen Y, He X, Gao J, et al (2014) Learning semantic representations using convolutional neural networks for web search. In: Proceedings of the 23rd International Conference on World Wide Web. ACM, pp 373\u2013374","DOI":"10.1145\/2567948.2577348"},{"key":"1710_CR85","first-page":"2493","volume":"12","author":"R Collobert","year":"2011","unstructured":"Collobert R, Weston J, Bottou L et al (2011) Natural language processing (almost) from scratch. J Mach Learn Res 12:2493\u20132537","journal-title":"J Mach Learn Res"},{"key":"1710_CR86","unstructured":"Liu P, Qiu X, Huang X (2016) Recurrent neural network for text classification with multi-task learning. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp 2873\u20132879."},{"key":"1710_CR87","doi-asserted-by":"crossref","unstructured":"Golmohammadi M, Ziyabari S, Shah V, et al (2017) Gated recurrent networks for seizure detection. In: 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017\u2014Proceedings. IEEE, pp 1\u20135.","DOI":"10.1109\/SPMB.2017.8257020"},{"key":"1710_CR88","doi-asserted-by":"crossref","unstructured":"Cheng F, Zhao J (2019) A novel process monitoring approach based on feature points distance dynamic autoencoder. In: Computer Aided Chemical Engineering (Vol. 46). Elsevier, pp 757\u2013762","DOI":"10.1016\/B978-0-12-818634-3.50127-2"},{"key":"1710_CR89","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9:1735\u20131780","journal-title":"Neural Comput"},{"key":"1710_CR90","doi-asserted-by":"publisher","unstructured":"Zhou C, Sun C, Liu Z, Lau F (2015) A C-LSTM neural network for text classification. Retrieved from https:\/\/doi.org\/10.48550\/arXiv.1511.08630","DOI":"10.48550\/arXiv.1511.08630"},{"key":"1710_CR91","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1016\/j.engappai.2006.09.001","volume":"20","author":"JJ Garc\u00eda Adeva","year":"2007","unstructured":"Garc\u00eda Adeva JJ, Pikatza Atxa JM (2007) Intrusion detection in web applications using text mining. Eng Appl Artif Intell 20:555\u2013566","journal-title":"Eng Appl Artif Intell"},{"key":"1710_CR92","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.1177\/0735633120940956","volume":"58","author":"T Hao","year":"2020","unstructured":"Hao T, Chen X, Song Y (2020) A topic-based bibliometric analysis of two decades of research on the application of technology in classroom dialogue. J Educ Comput Res 58:1311\u20131341","journal-title":"J Educ Comput Res"},{"key":"1710_CR93","doi-asserted-by":"crossref","unstructured":"Chen X, Gao D, Lun Y, et al (2019) The Analysis of Worldwide Research on Artificial Intelligence Assisted User Modeling. In: International Symposium on Emerging Technologies for Education. Springer, pp 201\u2013213","DOI":"10.1007\/978-3-030-38778-5_23"},{"key":"1710_CR94","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1504\/IJMLO.2022.119952","volume":"16","author":"X Chen","year":"2022","unstructured":"Chen X, Zou D, Xie H et al (2022) A bibliometric analysis of game-based collaborative learning between 2000 and 2019. Int J Mob Learn Organ 16:20\u201351","journal-title":"Int J Mob Learn Organ"},{"key":"1710_CR95","first-page":"151","volume":"25","author":"X Chen","year":"2021","unstructured":"Chen X, Zou D, Su F (2021) Twenty-five years of computer-assisted language learning: a topic modeling analysis. Lang Learn Technol 25:151\u2013185","journal-title":"Lang Learn Technol"},{"key":"1710_CR96","doi-asserted-by":"crossref","unstructured":"Yesir S, So\u011fukpinar \u0130 (2021) Malware Detection and Classification Using fastText and BERT. In: 2021 9th International Symposium on Digital Forensics and Security (ISDFS). IEEE, pp 1\u20136","DOI":"10.1109\/ISDFS52919.2021.9486377"},{"key":"1710_CR97","doi-asserted-by":"crossref","unstructured":"Sia S, Dalmia A, Mielke SJ (2020) Tired of topic models? clusters of pretrained word embeddings make for fast and good topics too! In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp 1728\u20131736.","DOI":"10.18653\/v1\/2020.emnlp-main.135"},{"key":"1710_CR98","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2020.102361","volume":"57","author":"B Oral","year":"2020","unstructured":"Oral B, Emekligil E, Arslan S, Eryi\u01e7it G (2020) Information extraction from text intensive and visually rich banking documents. Inf Process Manag 57:102361","journal-title":"Inf Process Manag"},{"key":"1710_CR99","doi-asserted-by":"crossref","unstructured":"Dufter P, Kassner N, Sch\u00fctze H (2021) Static Embeddings as Efficient Knowledge Bases? In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp 2353\u20132363","DOI":"10.18653\/v1\/2021.naacl-main.186"},{"key":"1710_CR100","doi-asserted-by":"crossref","first-page":"2184","DOI":"10.1093\/jamia\/ocab114","volume":"28","author":"A Magge","year":"2021","unstructured":"Magge A, Tutubalina E, Miftahutdinov Z et al (2021) DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter. J Am Med Inform Assoc 28:2184\u20132192","journal-title":"J Am Med Inform Assoc"},{"key":"1710_CR101","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbi.2020.103396","volume":"104","author":"NS Tawfik","year":"2020","unstructured":"Tawfik NS, Spruit MR (2020) Evaluating sentence representations for biomedical text: methods and experimental results. J Biomed Inform 104:103396","journal-title":"J Biomed Inform"},{"key":"1710_CR102","doi-asserted-by":"crossref","unstructured":"Immer A, Hennigen LT, Fortuin V, Cotterell R (2022) Probing as Quantifying Inductive Bias. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp 1839\u20131851","DOI":"10.18653\/v1\/2022.acl-long.129"},{"key":"1710_CR103","first-page":"100","volume":"100","author":"NNA Balaji","year":"2020","unstructured":"Balaji NNA, Bharathi B (2020) SSNCSE_NLP@ Fake news detection in the Urdu language (UrduFake) 2020. Health (Irvine Calif) 100:100","journal-title":"Health (Irvine Calif)"},{"key":"1710_CR104","doi-asserted-by":"crossref","unstructured":"Zarate JMO de, Giovanni M Di, Feuerstein EZ, Brambilla M (2020) Measuring controversy in social networks through nlp. In: International Symposium on String Processing and Information Retrieval. Springer, pp 194\u2013209","DOI":"10.1007\/978-3-030-59212-7_14"},{"key":"1710_CR105","doi-asserted-by":"crossref","unstructured":"Hennigen LT, Williams A, Cotterell R (2020) Intrinsic probing through dimension selection. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp 197\u2013216.","DOI":"10.18653\/v1\/2020.emnlp-main.15"},{"key":"1710_CR106","doi-asserted-by":"crossref","unstructured":"Liu Z, Winata GI, Fung P (2020) Zero-resource cross-domain named entity recognition. In: Proceedings of the 5th Workshop on Representation Learning for NLP, pp 1\u20136.","DOI":"10.18653\/v1\/2020.repl4nlp-1.1"},{"key":"1710_CR107","doi-asserted-by":"publisher","unstructured":"Hofst\u00e4tter S, Hanbury A (2019) Let\u2019s measure run time! Extending the IR replicability infrastructure to include performance aspects. Retrieved from https:\/\/doi.org\/10.48550\/arXiv.1907.04614","DOI":"10.48550\/arXiv.1907.04614"},{"key":"1710_CR108","doi-asserted-by":"crossref","unstructured":"Islam KI, Islam MS, Amin MR (2020) Sentiment analysis in Bengali via transfer learning using multi-lingual BERT. In: 2020 23rd International Conference on Computer and Information Technology (ICCIT). IEEE, pp 1\u20135","DOI":"10.1109\/ICCIT51783.2020.9392653"},{"key":"1710_CR109","doi-asserted-by":"crossref","first-page":"1448","DOI":"10.1016\/j.ipm.2007.12.009","volume":"44","author":"T Kucukyilmaz","year":"2008","unstructured":"Kucukyilmaz T, Cambazoglu BB, Aykanat C, Can F (2008) Chat mining: predicting user and message attributes in computer-mediated communication. Inf Process Manag 44:1448\u20131466","journal-title":"Inf Process Manag"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01710-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-022-01710-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01710-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,18]],"date-time":"2023-03-18T08:23:58Z","timestamp":1679127838000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-022-01710-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,15]]},"references-count":109,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["1710"],"URL":"https:\/\/doi.org\/10.1007\/s13042-022-01710-8","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,15]]},"assertion":[{"value":"10 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 December 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}