{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T05:24:12Z","timestamp":1775798652409,"version":"3.50.1"},"reference-count":81,"publisher":"Elsevier","isbn-type":[{"value":"9780128114322","type":"print"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1016\/b978-0-12-809633-8.20461-5","type":"book-chapter","created":{"date-parts":[[2017,12,20]],"date-time":"2017-12-20T18:52:45Z","timestamp":1513795965000},"page":"384-402","source":"Crossref","is-referenced-by-count":23,"title":["Data Mining: Classification and Prediction"],"prefix":"10.1016","author":[{"given":"Alfonso","family":"Urso","sequence":"first","affiliation":[]},{"given":"Antonino","family":"Fiannaca","sequence":"additional","affiliation":[]},{"given":"Massimo","family":"La Rosa","sequence":"additional","affiliation":[]},{"given":"Valentina","family":"Rav\u00ec","sequence":"additional","affiliation":[]},{"given":"Riccardo","family":"Rizzo","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib1","series-title":"Advances in Knowledge Discovery and Data Mining","first-page":"307","article-title":"Fast discovery of association rules","author":"Agrawal","year":"1995"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib2","unstructured":"Agrawal, R., Srikant R., 1994. Fast algorithms for mining association rules. In: Proceedings of International Conference on Very Large Data Bases (VLDB), San Jose, CA."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib3","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Tomasz I., Swami, A., 1993. Mining association rules between sets of items in large databases. In: Buneman, P., Jajodia, S. (Eds.), Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp. 207\u2013216. New York, NY: ACM.","DOI":"10.1145\/170035.170072"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib4","series-title":"Bioinformatics and Computational Biology","first-page":"1","article-title":"Association analysis techniques for bioinformatics problems","author":"Atluri","year":"2009"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib5","doi-asserted-by":"crossref","unstructured":"Baralis, E., Chiusano, S., Garza, P., 2004. On support thresholds in associative classification. In: Proceedings of the 2004 ACM Symposium on Applied Computing, pp. 553\u2013558. New York, NY: ACM.","DOI":"10.1145\/967900.968016"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib6","series-title":"Classification and Regression Trees","author":"Breiman","year":"1984"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib7","doi-asserted-by":"crossref","unstructured":"Brin, S., Motwani, R., Silverstein, C., 1997. Beyond market baskets: Generalizing associations rules to correlations. In: Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, pp. 265\u2013276. New York, NY: ACM.","DOI":"10.1145\/253260.253327"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib8","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/S0020-7373(87)80003-2","article-title":"PRISM: An algorithm for inducing modular rules","volume":"27","author":"Cendrowska","year":"1987","journal-title":"International Journal of ManMachine Studies"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib9","first-page":"1","article-title":"Data mining for the internet of things: Literature review and challenges","volume":"2015","author":"Chen","year":"2015","journal-title":"International Journal of Distributed Sensor Network"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib10","series-title":"Data Mining","first-page":"289","article-title":"Unsupervised learning: Association rules","author":"Cios","year":"2007"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib11","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/BF00116835","article-title":"The CN2 induction algorithm","volume":"3","author":"Clark","year":"1989","journal-title":"Machine Learning"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib12","doi-asserted-by":"crossref","unstructured":"Cohen, W.W., 1995. Fast effective rule induction. In: Proceedings of the 12th International Conference on Machine Learning, pp. 115\u2013123. San Mateo, CA: Morgan and Kaufmann.","DOI":"10.1016\/B978-1-55860-377-6.50023-2"},{"issue":"3","key":"10.1016\/B978-0-12-809633-8.20461-5_bib13","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Machine Learning"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib14","first-page":"265","article-title":"On the algorithmic implementation of multiclass kernel-based machines","volume":"2","author":"Crammer","year":"2001","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib15","series-title":"An Introduction to Support Vector Machines","author":"Cristianini","year":"2000"},{"issue":"5","key":"10.1016\/B978-0-12-809633-8.20461-5_bib16","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/S1532-0464(03)00034-0","article-title":"Logistic regression and artificial neural network classification models: A methodology review","volume":"35","author":"Dreiseitl","year":"2002","journal-title":"Journal of Biomedical Informatics"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib17","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1023\/A:1006524209794","article-title":"Separate-and-conquer rule learning","volume":"13","author":"F\u00fcrnkranz","year":"1999","journal-title":"Artificial Intelligence Review"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib18","series-title":"Encyclopedia of Machine Learning","first-page":"875","article-title":"Rule learning","author":"F\u00fcrnkranz","year":"2010"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib19","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/s10994-005-5011-x","article-title":"Roc \u2018n\u2032rule learning \u2013 Towards a better understanding of covering algorithms","volume":"58","author":"F\u00fcrnkranz","year":"2005","journal-title":"Machine Learning"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib20","doi-asserted-by":"crossref","unstructured":"Gosain, A., Bhugra, M., 2013. A comprehensive survey of association rules on quantitative data in data mining. In: IEEE Conference Information & Communication Technologies, JeJu Island, pp. 1003\u20131008.","DOI":"10.1109\/CICT.2013.6558244"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib21","series-title":"Concepts and Techniques","article-title":"Data mining","author":"Han","year":"2012"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib22","doi-asserted-by":"crossref","unstructured":"Han, J., Pei, J., Yin, Y., 2000. Mining frequent patterns without candidate generation. In: Proceedings of the 2000 ACM SIGMOD International conference on Management of Data, pp. 1\u201312. New York, NY: ACM.","DOI":"10.1145\/342009.335372"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib222","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., Friedman J., 2008. The Elements of Statistical Learning, second ed. Stanford, CA: Springer.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib23","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1023\/A:1022631118932","article-title":"Very simple classification rules perform well on most commonly used datasets","volume":"11","author":"Holte","year":"1993","journal-title":"Machine Learning"},{"issue":"2","key":"10.1016\/B978-0-12-809633-8.20461-5_bib24","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1109\/72.991427","article-title":"A comparison of methods for multiclass support vector machines","volume":"13","author":"Hsu","year":"2002","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib25","series-title":"Concept Learning: An Information Processing Problem","author":"Hunt","year":"1962"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib26","series-title":"Experiments in Induction","author":"Hunt","year":"1966"},{"issue":"3","key":"10.1016\/B978-0-12-809633-8.20461-5_bib27","first-page":"31","article-title":"Artificial neural networks: A tutorial","volume":"29","author":"Jain","year":"1996","journal-title":"IEEE Computer-Special Issue in Neural Computing"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib28","doi-asserted-by":"crossref","unstructured":"Joachims, T., 1998. Text categorization with support vector machines: Learning with many relevant features. In: Hutchison, D., Kanade, T., Kittler, J., et al. (Eds.), Machine Learning: European Conference on Machine Learning (in LNCS 1398), pp. 137\u2013142. Berlin: Springer.","DOI":"10.1007\/BFb0026683"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib29","doi-asserted-by":"crossref","unstructured":"Kesavaraj, G., Sukumaran, S., 2013. A study on classification techniques in data mining. In: Proceedings of the International Conference on Computer Communication and Networking Technologies (ICCCNT\u05f313), pp. 1\u20137. Tamil Nadu: IEEE.","DOI":"10.1109\/ICCCNT.2013.6726842"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib30","series-title":"Advances in Kernel Methods: Support Vector Learning","first-page":"255","article-title":"Pairwise classification and support vector machines","author":"Kre\u00dfel","year":"1999"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib31","doi-asserted-by":"crossref","first-page":"30","DOI":"10.5120\/ijca2016910144","article-title":"Knowledge discovery in text mining using association rule extraction","volume":"143","author":"Kulkarni","year":"2016","journal-title":"International Journal of Computer Applications"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5120\/3095-4247","article-title":"Performance evaluation of decision tree classifiers on medical datasets","volume":"26","author":"Lavanya","year":"2011","journal-title":"International Journal of Computer Applications"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib33","first-page":"1137","article-title":"Rule-based classification systems using classification and regression trees (CART) analysis","volume":"67","author":"Lawrence","year":"2001","journal-title":"Photogrammetric Engineering & Remote Sensing"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib34","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib35","doi-asserted-by":"crossref","first-page":"2429","DOI":"10.1093\/bioinformatics\/bth267","article-title":"A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression","volume":"20","author":"Li","year":"2004","journal-title":"Bioinformatics"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib36","series-title":"Exploring Hyperlinks, Contents and Usage Data","article-title":"Web data mining","author":"Liu","year":"2011"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib37","unstructured":"Liu, B., Hsu, W., Ma, Y., 1998. Integrating classification and association rule mining. In: Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, pp. 80\u201386. New York, NY: AAAI Press."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib38","unstructured":"Li, W., Han, J., Pei, J., 2001. CMAR: Accurate and efficient classification based on multiple class-association rules. In: Proceedings of the IEEE International Conference on ICDM\u05f301, pp. 369\u2013376. IEEE: San Jose, CA."},{"issue":"4","key":"10.1016\/B978-0-12-809633-8.20461-5_bib39","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/BF02478259","article-title":"A logical calculus of the ideas immanent in nervous activity","volume":"5","author":"McCulloch","year":"1943","journal-title":"Bulletin of Mathematical Biophysics"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib40","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1109\/TPAMI.1980.4767034","article-title":"Pattern recognition as rule-guided induction inference","volume":"2","author":"Michalski","year":"1980","journal-title":"IEEE Transaction On Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib41","unstructured":"Michalski, R.S., 1969. On the quasi-minimal solution of the general covering problem. In: Proceeding of the V International Symposium on the Information Processing, Bled, Yugoslavia, pp 125\u2013128."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib42","unstructured":"Michalski, R.S., 1975. Synthesis of optimal and quasi-optimal variable-valued logic formulas. In: Proceedings of the 1975 International Symposium on Multiple-Valued Logic, pp. 76\u201387. Bloomington, Indiana."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib43","doi-asserted-by":"crossref","unstructured":"Minsky, M., 1961. Steps toward artificial intelligence. In: Hamburger, F. (Ed.), Proceedings of the IRE, vol. 49 (No. 1), pp. 8--30. New York: IEEE.","DOI":"10.1109\/JRPROC.1961.287775"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib46","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1023\/A:1022611825350","article-title":"Boolean feature discovery in empirical learning","volume":"5","author":"Pagallo","year":"1990","journal-title":"Machine Learning"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib47","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/BF00116251","article-title":"Induction of decision trees","volume":"1","author":"Quinlan","year":"1986","journal-title":"Machine Learning"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib48","series-title":"C4.5: Programs for Machine Learning","author":"Quinlan","year":"1993"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib49","first-page":"239","article-title":"Learning Logical Definitions from Relations","volume":"5","author":"Quinlan","year":"1990"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib50","doi-asserted-by":"crossref","unstructured":"Quinlan, J.R., Cameron-Jones, R.M., 1993. FOIL: A midterm report. In: Brazdil, P.B. (Ed.), Proceedings of European Conference on Machine Learning, pp. 3\u201320. Vienna: Springer-Verlag.","DOI":"10.1007\/3-540-56602-3_124"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib51","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1023\/B:AMAI.0000018580.96245.c6","article-title":"Theoretical comparison between the Gini Index and Information Gain criteria","volume":"41","author":"Raileanu","year":"2004","journal-title":"Annals of Mathematics and Artificial Intelligence"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib52","series-title":"Data Mining and Knowledge Discovery Handbook","first-page":"165","article-title":"Decision trees","author":"Rokach","year":"2005"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib54","series-title":"Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanism","author":"Rosenblatt","year":"1962"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib55","series-title":"A Systematic Introduction","article-title":"Neural Networks","author":"Royas","year":"1996"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib56","first-page":"318","article-title":"Learning internal representations by error propagation","volume":"1","author":"Rumelhart","year":"1986"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib57","unstructured":"Scholkopf, B., Burges, C., Vapnik, V., 1995. Extracting support data for a given task. In: Fayyad, U.M., Uthurusamy, R. (Eds.), Proceedings of the First International Conference on Knowledge discovery and Data Mining, pp. 252\u2013257. Menlo Park, CA: AAAI Press."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib58","series-title":"Introduction to Data Mining","author":"Tan","year":"2005"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib59","series-title":"The Nature of Statistical Learning Theory","author":"Vapnik","year":"1995"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib60","series-title":"Statistical Learning Theory","author":"Vapnik","year":"1998"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib61","series-title":"Support Vector Machines Applications","first-page":"23","article-title":"Multi-class support vector machine","author":"Wang","year":"2014"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib62","unstructured":"Weston, J., Watkins, C., 1999. Support vector machines for multi-class pattern recognition. In: Verleysen, M. (Ed.), Proceedings of European Symposium on Artificial Neural Networks, pp. 219\u2013224. Bruges: ESANN."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib63","unstructured":"Widrow, B., Hoff, M.E., 1960. Adaptive switching circuits. In: IRE WESCON Convention Record, vol. 4, pp. 96\u2013104. Reprinted in Anderson and Rosenfeld (1988)."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10115-007-0114-2","article-title":"Top 10 algorithms in data mining","volume":"14","author":"Wu","year":"2008","journal-title":"Knowledge and Information Systems"},{"issue":"10","key":"10.1016\/B978-0-12-809633-8.20461-5_bib65","doi-asserted-by":"crossref","first-page":"1796","DOI":"10.1360\/crad20051024","article-title":"Feature selection for cancer classification based on support vector machine","volume":"42","author":"Yingxin","year":"2005","journal-title":"Journal of Computer Research and Development"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib66","doi-asserted-by":"crossref","unstructured":"Yin, X., Han, J., 2003. CPAR: Classification based on predictive association rules. In: Barbara, D., Kamath, C. (Eds.), Proceedings of the 2003 SIAM International Conference on Data Mining, pp. 331\u2013335. San Francisco, CA: Society for Industrial and Applied Mathematics.","DOI":"10.1137\/1.9781611972733.40"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_bib67","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.inffus.2016.11.009","article-title":"One versus one multi-class classification fusion using optimizing decision directed acyclic graph for predicting listing status of companies","volume":"36","author":"Zhou","year":"2017","journal-title":"Information Fusion"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur1","series-title":"Neural Networks for Pattern Recognition","author":"Bishop","year":"1995"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur2","series-title":"Pattern Recognition and Machine Learning","author":"Bishop","year":"2006"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur3","series-title":"Pattern Classification","author":"Duda","year":"1991"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur4","series-title":"Machine Learning","author":"Flach","year":"2012"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur6","series-title":"Machine Learning in Action","author":"Harrinton","year":"2012"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur7","series-title":"Information Theory, Inference and Learning Algorithms","author":"MacKay","year":"2005"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur8","series-title":"Python for Data Analysis","author":"McKinney","year":"2012"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur9","series-title":"Machine Learning","author":"Mitchell","year":"1997"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur10","series-title":"Bioinformatics Programmingusing Python","author":"Model","year":"2009"},{"issue":"2","key":"10.1016\/B978-0-12-809633-8.20461-5_fur11","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1109\/72.914517","article-title":"An introduction to kernel-based learning algorithms","volume":"12","author":"Muller","year":"2001","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur12","unstructured":"Phyu, T.N., 2009. Survey of classification techniques in data mining. In: Ao, S.I., Castillo, O., Douglas, C., Feng, D.D., Lee, J.A. (Eds.), Proceedings of International Multi-Conference of Engineers and Computer Scientists, pp. 727\u2013731. Hong Kong: Newswood Limited."},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur13","series-title":"Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond","author":"Sch\u00f6lkopf","year":"2002"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur14","series-title":"Kernel Methods for Pattern Analysis","author":"Shawe-Taylor","year":"2004"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur15","first-page":"1453","article-title":"Large margin methods for structured and interdependent output variables","volume":"6","author":"Tsochantaridis","year":"2005","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur16","series-title":"Data Mining: Practical Machine Learnig Tools and Techniques","author":"Witten","year":"2005"},{"key":"10.1016\/B978-0-12-809633-8.20461-5_fur17","series-title":"The Top Ten Algorithms in Data Mining","author":"Wu","year":"2009"}],"container-title":["Encyclopedia of Bioinformatics and Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:B9780128096338204615?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:B9780128096338204615?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2022,8,10]],"date-time":"2022-08-10T19:18:06Z","timestamp":1660159086000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/B9780128096338204615"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9780128114322"],"references-count":81,"URL":"https:\/\/doi.org\/10.1016\/b978-0-12-809633-8.20461-5","relation":{},"subject":[],"published":{"date-parts":[[2019]]}}}