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Article

Nascimento, S. and Casca, S. and Mirkin, Boris (2015) A seed expanding cluster algorithm for deriving upwelling areas on sea surface temperature images. Computers & Geosciences 85 (B), pp. 74-85. ISSN 0098-3004.

Nascimento, S. and Felizardo, R. and Mirkin, Boris (2013) Laplacian normalization for deriving thematic fuzzy clusters with an additive spectral approach. Expert Systems , ISSN 0266-4720.

Mirkin, Boris and Nascimento, S. (2012) Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices. Information Sciences 183 (1), pp. 16-34. ISSN 0020-0255.

Mirkin, Boris and Fenner, Trevor and Nascimento, S. and Moniz Pereira, L. (2010) Building fuzzy thematic clusters and mapping them to higher ranks in a taxonomy. International Journal of Software and Informatics 4 (3), pp. 257-275. ISSN 1673-7288.

Mirkin, Boris and Nascimento, S. and Pereira, L.M. (2010) Cluster-lift method for mapping research activities over a concept tree. Studies in Computational Intelligence 263 , pp. 245-257. ISSN 1860-949X.

Mirkin, Boris and Nascimento, S. and Pereira, L.M. (2008) Representing a computer science research organization on the ACM computing classification system. Supplementary Proceedings of the 16th International Conference on Conceptual Structures 354 , pp. 57-65. ISSN 1613-0073.

Book Section

Nascimento, S. and Mirkin, Boris (2017) Applying anomalous cluster approach to spatial clustering. In: Kreinovich, V. (ed.) Uncertainty Modeling. Studies in Computational Intelligence 683. Springer, pp. 147-157. ISBN 9783319510514.

Mirkin, Boris and Nascimento, S. (2011) Developing additive spectral approach to fuzzy clustering. In: Kuznetsov, S.O. and Ślęzak, D. and Hepting, D.H. and Mirkin, Boris (eds.) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. Lecture Notes in Computer Science 6743. Berlin, Germany: Springer Verlag, pp. 273-277. ISBN 9783642218804.

Mirkin, Boris and Nascimento, S. and Fenner, Trevor and Felizardo, R. (2011) How to visualize a crisp or fuzzy topic set over a taxonomy. In: Kuznetsov, S.O. and Mandal, D.P. and Kundu, M.K. and Pal, S.K (eds.) Pattern Recognition and Machine Intelligence. Lecture Notes in Computer Science 6744 6744. Berlin, Germany: Springer Verlag, pp. 3-12. ISBN 9783642217869.

Nascimento, S. and Felizardo, R. and Mirkin, Boris (2011) Thematic fuzzy clusters with an additive spectral approach. In: Antunes, L. and Pinto, S.H. (eds.) Progress in Artificial Intelligence. Berlin, Germany: Springer Verlag, pp. 446-461. ISBN 9783642247682.

Mirkin, Boris and Nascimento, S. and Fenner, Trevor and Pereira, L.M. (2010) Constructing and mapping fuzzy thematic clusters to higher ranks in a taxonomy. In: Bi, Y. and Williams, M.A. (eds.) Knowledge Science, Engineering and Management. Lecture Notes in Computer Science 6291. Berlin, Germany: Springer Verlag, pp. 329-340. ISBN 9783642152801.

Mirkin, Boris and Nascimento, S. and Fenner, Trevor and Pereira, L.M. (2010) A hybrid cluster-lift method for the analysis of research activities. In: Romay, M. and GranaSebastian, M. and Garcia, T. (eds.) Hybrid Artificial Intelligence Systems. Lecture Notes in Artificial Intelligence 1 6076. Berlin, Germany: Springer Verlag, pp. 152-161. ISBN 9783642137693.

Conference or Workshop Item

Hayrapetyan, Z. and Mirkin, Boris and Nascimento, S. and Fenner, Trevor and Frolov, D. (2023) Modeling a most specific generalization in domain taxonomies. In: 17th Conference of the International Federation of Classification Societies (IFCS 2022), 19-23 July 2022, Porto, Portugal. (In Press)