JADT 2022. 6. Bibliography

6. Bibliography

Arbelaitz, O., Gurrutxaga, I., Muguerza, J., Pérez, J.M. and Perona, I. (2013). An extensive comparative study of cluster validity indices, Pattern Recognition, Volume 46, Issue 1, pp. 243-256.

Bécue-Bertaut, M., Alvarez-Esteban, R, Sánchez-Espigares, J.A. and Kostov, B. (2022). Xplortext: statistical analysis of textual data. R package version 1.5.

Borcard, D., F. Gillet and P. Legendre. (2018). Numerical ecology with R, 2nd edition. Use R! series, Springer International Publishing AG. xv+ 435 pp.

Gançarski, P., Dao, TBH, D., Crémilleux, B., Forestier, F. and Lamper, T. (2020). Constrained clustering current and new trends. A guided tour of AI research. Springer. hal-02548212.

Gordon, A. D. (1999). Classification. 2nd ed. Boca Raton, FL: Chapman & Hall/CRC.

Lebart, L. (1978). Programme d’agrégation avec contraintes [C.A.H. Contiguité], Les Cahiers de l’Analyse des Données, 3, 275–287.

Legendre, P. and Legendre, L. (2012). Numerical Ecology (3nd ed.), Elsevier Science BV, Amsterdam.

Legendre, P., Dallot, S. and Legendre, L. (1985). Succession of species within a community: chronological clustering, with applications to marine and freshwater zooplankton, American Naturalist, 125, 257–288.

Milligan, G. W., and Cooper, M.C. (1985). An examination of procedures for determining the number of clusters in a dataset. Psychometrika 50: 159–179.

Nielsen, F. (2016). Hierarchical clustering. In: Introduction to HPC with MPI for data science. Undergraduate topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-21903-5_8