No Access

BIBLIOMETRIC MAPPING OF THE COMPUTATIONAL INTELLIGENCE FIELD

Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands

Search for more papers by this author

and

LUDO WALTMAN

Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands

Search for more papers by this author

https://doi.org/10.1142/S0218488507004911Cited by:219 (Source: Crossref)

Abstract

In this paper, a bibliometric study of the computational intelligence field is presented. Bibliometric maps showing the associations between the main concepts in the field are provided for the periods 1996–2000 and 2001–2005. Both the current structure of the field and the evolution of the field over the last decade are analyzed. In addition, a number of emerging areas in the field are identified. It turns out that computational intelligence can best be seen as a field that is structured around four important types of problems, namely control problems, classification problems, regression problems, and optimization problems. Within the computational intelligence field, the neural networks and fuzzy systems subfields are fairly intertwined, whereas the evolutionary computation subfield has a relatively independent position.

Keywords:

References

A. F. J. van Raan and R. J. W. Tijssen, Scientometrics 26(1), 169 (1993), DOI: 10.1007/BF02016799. Crossref, Web of Science, Google Scholar
E. C. M. Noyons and A. F. J. van Raan, J. Am. Soc. Inf. Sci. Tec. 49(1), 68 (1998). Web of Science, Google Scholar
N. J. van Ecket al., Visualizing the WCCI 2006 knowledge domain, Proc. 2006 IEEE Int. Conf. Fuzzy Systems (2006) pp. 7862–7869. Google Scholar
N. J. van Ecket al., IEEE Computational Intelligence Magazine 1(4), 6 (2006). Google Scholar
K. Börner, C. Chen and K. W. Boyack, Annu. Rev. Inform. Sci. 37, 179 (2003). Crossref, Google Scholar
E. C. M. Noyons, Handbook of Quantitative Science and Technology Research, eds. H. F. Moed, W. Glänzel and U. Schmoch (Kluwer Academic Publishers, 2004) pp. 237–255. Crossref, Google Scholar
C. Chen , Information Visualization: Beyond the Horizon , 2nd edn. ( Springer , 2006 ) . Google Scholar
I. Borg and P. J. F. Groenen , Modern Multidimensional Scaling , 2nd edn. ( Springer , 2005 ) . Google Scholar
K. W. McCain, J. Am. Soc. Inf. Sci. 41(6), 433 (1990). Crossref, Web of Science, Google Scholar
H. D. White and K. W. McCain, J. Am. Soc. Inf. Sci. Tec. 49(4), 327 (1998). Web of Science, Google Scholar
J. D. Novak and D. B. Gowin , Learning How to Learn ( Cambridge University Press , 1984 ) . Crossref, Google Scholar
H. P. F. Peters and A. F. J. van Raan, Research Policy 22, 23 (1993), DOI: 10.1016/0048-7333(93)90031-C. Crossref, Web of Science, Google Scholar
S. Hinze, Scientometrics 29(3), 353 (1994), DOI: 10.1007/BF02033445. Crossref, Web of Science, Google Scholar
J. S. Justeson and S. M. Katz, Natural Language Engineering 1, 9 (1995), DOI: 10.1017/S1351324900000048. Crossref, Google Scholar
A. Rip and J.-P. Courtial, Scientometrics 6(6), 381 (1984), DOI: 10.1007/BF02025827. Crossref, Web of Science, Google Scholar
N. J. van Eck and L. Waltman, VOS: a new method for visualizing similarities between objects, Advances in Data Analysis: Proc. 30th Ann. Conf. German Classification Society, Studies in Classification, Data Analysis, and Knowledge Organization (Springer, 2007) pp. 299–306. Google Scholar
N. J. van Eck, F. Frasincar and J. van den Berg, Visualizing concept associations using concept density maps, Proc. 10th Int. Conf. Information Visualisation (2006) pp. 270–275. Google Scholar
D. W. Scott , Multivariate Density Estimation ( John Wiley & Sons , 1992 ) . Crossref, Google Scholar
J. de Leeuw and J. Meulman, J. Classif. 3, 97 (1986), DOI: 10.1007/BF01896814. Crossref, Web of Science, Google Scholar
W. J. Heiser and J. Meulman, J. of Econometrics 22, 139 (1983), DOI: 10.1016/0304-4076(83)90097-0. Crossref, Web of Science, Google Scholar
W. J. Heiser and J. Meulman, Appl. Psych. Meas. 7, 381 (1983), DOI: 10.1177/014662168300700402. Crossref, Web of Science, Google Scholar
S. L. Weinberg, J. D. Carroll and H. S. Cohen, Psychometrika 49(4), 475 (1984), DOI: 10.1007/BF02302586. Crossref, Web of Science, Google Scholar
A. P. Engelbrecht , Computational Intelligence: An Introduction ( John Wiley & Sons , 2003 ) . Google Scholar
A. Konar , Computational Intelligence: Principles, Techniques and Applications ( Springer , 2005 ) . Crossref, Google Scholar