Abstract
International Journal of Machine Learning and Cybernetics (IJMLC) is one of the influential journals in the area of computer science, and it published its first issue in 2010. On the one hand, taking the 544 IJMLC publications between 2010 and 2017 as the research object, this paper uses bibliometric methods to study the citation characteristics, international cooperation and institutional cooperation, the author’s cooperation rate and cooperation degree, geographical distribution of the IJMLC publications. On the other hand, CiteSpace and Vosviewer, two data visualization software tools, are used to make the comprehensive analysis of the co-occurrence of the author keywords of the IJMLC publications. The document co-citation clusters visualization and burst detection of keywords are also presented to explore the development of the research trends. The research results in this paper provide a basis for further improving the academic level and quality of the IJMLC.
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References
Akmal A, Podgorodnichenko N, Greatbanks R, Everett AM (2018) Bibliometric analysis of production planning and control (1990–2016). Prod Plan Control 29(4):333–351
Biggio B, Fumera G, Roli F (2010) Multiple classifier systems for robust classifier design in adversarial environments. Int J Mach Learn Cybern 1(1–4):27–41
Boehm O, Hardoon DR, Manevitz LM (2011) Classifying cognitive states of brain activity via one–class neural networks with feature selection by genetic algorithms. Int J Mach Learn Cybern 2(3):125–134
Borgman CL, Furner J (2002) Scholarly communication and bibliometrics. Ann Rev Inf Sci Technol 36(1):1–53
Cancino C, Merigó JM, Coronado F, Dessouky Y, Dessouky M (2017) Forty years of computers and industrial engineering: a bibliometric analysis. Comput Ind Eng 113:614–629
Castillo-Vergara M, Alvarez-Marin A, Placencio-Hidalgo D (2018) A bibliometric analysis of creativity in the field of business economics. J Bus Res 85:1–9
Chacko BP, Krishnan VRV, Raju G, Anto PB (2012) Handwritten character recognition using wavelet energy and extreme learning machine. Int J Mach Learn Cybern 3(2):149–161
Chau KW (2007) Application of a PSO based neural network in analysis of outcomes of construction claims. Autom Constr 16(5):642–646
Chen C (2006) CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J Assoc Inf Sci Technol 57(3):359–377
Chen C, Ibekwe-SanJuan F, Hou J (2010) The structure and dynamics of co-citation clusters: a multiple-perspective cocitation analysis. J Assoc Inf Sci Technol 61(7):1386–1409
Cobo MJ, Martínez MA, Gutiérrez-Salcedo M, Fujita H, Herrera-Viedma E (2015) 25 years at knowledge-based systems: a bibliometric analysis. Knowl Based Syst 80:3–13
Fang Y (2015) Visualizing the structure and the evolving of digital medicine: a scientometrics review. Scientometrics 105(1):5–21
Graaff AJ, Engelbrecht AP (2012) Clustering data in stationary environments with a local network neighborhood artificial immune system. Int J Mach Learn Cybern 3(1):1–26
Gaede J, Rowlands IH (2018) Visualizing social acceptance research: a bibliometric review of the social acceptance literature for energy technology and fuels. Energy Res Soc Sci 40:142–158
Hirsch JE (2005) An index to quantify an individual’s scientific research output. Proc Natl Acad Sci USA 102(46):16569–16572
Hood W, Wilson C (2001) The literature of bibliometrics, scientometrics, and informetrics. Scientometrics 52(2):291–314
Hu QH, Pan W, An S, Ma PJ, Wei JM (2010) An efficient gene selection technique for cancer recognition based on neighborhood mutual information. Int J Mach Learn Cybern 1(1–4):63–74
Hu Y, Sun J, Li W, Pan Y (2014) A scientometric study of global electric vehicle research. Scientometrics 98(2):1269–1282
Huang F, Zhou Q, Leng BJ, Mao QL, Zheng LM, Zuo MZ (2018) A bibliometric and social network analysis of pelvic organ prolapse during 2007–2016. J Chin Med Assoc 81(5):450–457
Huang GB, Chen L (2007) Convex incremental extreme learning machine. Neurocomputing 70(16–18):3056–3062
Huang GB, Wang DH, Lan Y (2011) Extreme learning machines: a survey. Int J Mach Learn Cybern 2(2):107–122
Jun W, Wang ST, Chung FL (2011) Positive and negative fuzzy rule system, extreme learning machine and image classification. Int J Mach Learn Cybern 2(4):261–271
Kim MC, Chen C (2015) A scientometric review of emerging trends and new developments in recommendation systems. Scientometrics 104(1):239–263
Laengle S, Merigó JM, Miranda J, Słowiński R, Bomze I, Borgonovo E, Teunter R (2017) Forty years of the European Journal of Operational Research: a bibliometric overview. Eur J Oper Res 262(3):803–816
Lan Y, Soh YC, Huang GB (2009) Ensemble of online sequential extreme learning machine. Neurocomputing 72(13–15):3391–3395
Leydesdorff L, Vaughan L (2006) Co-occurrence matrices and their applications in information science: extending ACA to the Web environment. J Assoc Inf Sci Technol 57(12):1616–1628
Li MB, Huang GB, Saratchandran P, Sundararajan N (2005) Fully complex extreme learning machine. Neurocomputing 68:306–314
Li JH, Mei CL, Kumar CA, Zhang X (2013) On rule acquisition in decision formal contexts. Int J Mach Learn Cybern 4(6):721–731
Liang J, Song W (2012) Clustering based on Steiner points. Int J Mach Learn Cybern 3(2):141–148
Liu N, Wang H (2010) Ensemble based extreme learning machine. IEEE Signal Process Lett 17(8):754–757
Liu Z, Wu Q, Zhang Y, Chen CP (2011) Adaptive least squares support vector machines filter for hand tremor canceling in microsurgery. Int J Mach Learn Cybern 2(1):37–47
Merigó JM, Blanco-Mesa F, Gil-Lafuente AM, Yager RR (2017) Thirty years of the International Journal of Intelligent Systems: a bibliometric review. Int J Intell Syst 32(5):526–554
Merigó JM, Yang JB (2017) A bibliometric analysis of operations research and management science. Omega 73:37–48
Pritchard A (1969) Statistical bibliography or bibliometrics. J Doc 25(4):348–349
Rana S, Jasola S, Kumar R (2013) A boundary restricted adaptive particle swarm optimization for data clustering. Int J Mach Learn Cybern 4(4):391–400
Sharma A, Imoto S, Miyano S, Sharma V (2012) Null space based feature selection method for gene expression data. Int J Mach Learn Cybern 3(4):269–276
Tang Y, Yan PK, Yuan Y, Li XL (2011) Single-image super-resolution via local learning. Int J Mach Learn Cybern 2(1):15–23
Tong DL, Mintram R (2010) Genetic algorithm-neural network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection. Int J Mach Learn Cybern 1(1–4):75–87
Tsang EC, Wang XZ, Yeung DS (2000) Improving learning accuracy of fuzzy decision trees by hybrid neural networks. IEEE Trans Fuzzy Syst 8(5):601–614
Van Eck NJ, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2):523–538
Waltman L, van Eck NJ, Noyons EC (2010) A unified approach to mapping and clustering of bibliometric networks. J Inf 4(4):629–635
Wang XZ, He YL, Dong LC, Zhao HY (2011) Particle swarm optimization for determining fuzzy measures from data. Inf Sci 181(19):4230–4252
Wang XZ, Zhai JH, Lu SX (2008) Induction of multiple fuzzy decision trees based on rough set technique. Inf Sci 178(16):3188–3202
Wei GW (2016) Interval valued hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making. Int J Mach Learn Cybern 7(6):1093–1114
White HD, McCain KW (1998) Visualizing a discipline: an author co-citation analysis of information science, 1972–1995. J Am Soc Inf Sci 49(4):327–355
Xiao JZ, Wang HR, Yang XC, Gao Z (2012) Multiple faults diagnosis in motion system based on SVM. Int J Mach Learn Cybern 3(1):77–82
Yang XB, Song XN, Chen ZH, Yang JY (2012) On multigranulation rough sets in incomplete information system. Int J Mach Learn Cybern 3(3):223–232
Ye S, Xing R, Liu J, Xing F (2013) Bibliometric analysis of Nobelists’ awards and landmark papers in physiology or medicine during 1983–2012. Ann Med 45(8):532–538
Yi WG, Lu MY, Liu Z (2011) Multi-valued attribute and multi-labeled data decision tree algorithm. Int J Mach Learn Cybern 2(2):67–74
Yu DJ, Xu ZS, Pedrycz W, Wang WR (2017) Information sciences 1968–2016: a retrospective analysis with text mining and bibliometric. Inf Sci 418:619–634
Yu DJ, Xu ZS, Wang WR (2018) Bibliometric analysis of fuzzy theory research in China: a 30-year perspective. Knowl Based Syst 141:188–199
Yu DJ, Xu ZS, Kao Y, Lin CT (2018) The structure and citation landscape of IEEE Transactions on Fuzzy Systems (1994–2015). IEEE Trans Fuzzy Syst 26(2):430–442
Yu DJ, Xu ZS, Fujita H (2018) Bibliometric analysis on the evolution of applied intelligence. Appl Intell. https://doi.org/10.1007/s10489-018-1278-z
Zhang Y, Jin R, Zhou ZH (2010) Understanding bag-of-words model: a statistical framework. Int J Mach Learn Cybern 1(1–4):43–52
Zhu W, Wang SP (2011) Matroidal approaches to generalized rough sets based on relations. Int J Mach Learn Cybern 2(4):273–279
Acknowledgements
The work was supported in part by the China National Natural Science Foundation (nos. 71771155, 71571123).
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Xu, Z., Yu, D. & Wang, X. A bibliometric overview of International Journal of Machine Learning and Cybernetics between 2010 and 2017. Int. J. Mach. Learn. & Cyber. 10, 2375–2387 (2019). https://doi.org/10.1007/s13042-018-0875-9
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DOI: https://doi.org/10.1007/s13042-018-0875-9