caa a22 4500 465754767 CHVBK 20180323111844.0 cr unu---uuuuu 170327e19901201xx s 000 0 eng 10.1007/BF01170014 doi (NATIONALLICENCE)springer-10.1007/BF01170014 Similarity measures for sets of strings and application in chemical classification [Elektronische Daten] [Borka Jerman-Blažič, Milan Randić] This paper introduces new ideas for quantification of the similarity between chemical compounds. The method adopted makes use of similarity measures derived through comparison of two strings. The derived data on the similarity are then analyzed and applied in the identification of clusters in which the entities are more homogeneous and similar than those outside a cluster. J.C. Baltzer AG, Scientific Publishing Company, 1990 Jerman-Blažič Borka Institut Jožef Stefan, E. Kardelj University, Ljubljana, Yugoslavia aut Randić Milan Department of Computer Science, Drake University, 50311, Des Moines, Iowa, USA aut Journal of Mathematical Chemistry Kluwer Academic Publishers 4/1(1990-12-01), 217-225 0259-9791 4:1<217 1990 4 10910 https://doi.org/10.1007/BF01170014 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01170014 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Jerman-Blažič Borka Institut Jožef Stefan, E. Kardelj University, Ljubljana, Yugoslavia aut NATIONALLICENCE 700 1- Randić Milan Department of Computer Science, Drake University, 50311, Des Moines, Iowa, USA aut NATIONALLICENCE 773 0- Journal of Mathematical Chemistry Kluwer Academic Publishers 4/1(1990-12-01), 217-225 0259-9791 4:1<217 1990 4 10910 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer