A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

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Keywords Automatic term identification, Bibliometric mapping, Operations research, Probabilistic latent semantic analysis, Term map
Persistent URL dx.doi.org/10.1007/s11192-010-0173-0, hdl.handle.net/1765/19808
van Eck, N.J.P, Waltman, L, Noyons, E.C.M, & Buter, R.K. (2010). Automatic term identification for bibliometric mapping. Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy, 82(3), 581–596. doi:10.1007/s11192-010-0173-0