home
about ISKO
join ISKO
Knowledge Organization journal
ISKO events
ISKO chapters
ISKO people
ISKO publications
Encyclopedia
KO literature
KO institutions
⇗ KOS registry
🔒 members
contact us
|
Knowledge organization literature. Selected items
Your search for
class 253 Classification Procedures
found the 22 items below.
[new search]
Items on this class as the base theme
Whitelaw, Lara, et al. – Pragmatic support for taxonomy-based annotation of structured digital documents (Lang.: eng). - In: Electronic library, 27(2009) 5, pp. 755-756. Chaudhry, Abdus Sattar. – Assessment of taxonomy building tools (Lang.: eng). - In: Electronic library, 28(2010)6, pp. 769-788. Cataldi, M., Candan, K. S., Sapino, M. L. – Narrative-based taxonomy distillation for effective indexing of text collections (Lang.: eng). - In: Data and knowledge engineering, 72(2012), pp. 103-125. Tubbs, J.D.; Alltop, W.O. – Measures of confidence associated with combining classification results (Lang.: eng). - In: IEEE Transact.on Syst.,Man &.Vol.21.No.3.1991.p.690-692. Shiaw-Dong, D.L.; Casasent, D.P. – Iterative Fisher/Minimum-Variance optical classifier (Lang.: eng). - In: Pattern Recognition.Vol.23.No.3/4.1990.p.385-391. Broder, A.J. – Strategies for efficient incremental nearest neighbor search (Lang.: eng). - In: Üattern Recognition.Vol.23.No.1/2.1990.p.171-178. Huang, J.S.; Shieh, W.R. – A heuristic method for separating clusters form noisy background (Lang.: eng). - In: Pattern Recognition.Vol.23.No.1/2.1990.p.147-157. Granovsky, Yu.V.; Luibimova, T.N., Murashova, T.I., Myatlev, V.D.. – Information-based evaluation of the quality of doctoral theses (Lang.: eng). - In: ScientometricsVol. 23 No. 3. 1992. p.361-376. Thom, J.A.; Zobel, J.. – A model for word clustering (Lang.: eng). - In: J.Amer.Soc.Inform.Sci.Vol. 43 No. 9. 1992. p.616-627. Tubbs, J.D.; Alltop, W.O.. – Measures of confidence associated with combining classification results (Lang.: eng). - In: IEEE Transact.on Syst.,Man &... Vol. 21. No. 3. p.690-692. Shah, K.L.. – Interpreting readership data: a new multivariate approach through visualization (Lang.: eng). - In: Libr.Sci.Slant Doc.Inf.Stud.. 30(1993)3,p.103-117. Multivariate Analysis is a fresh wave of data analysis in informetrics in general and the readership data in particular, where most of the data are continuous or/and categorical. The already published categorical data are popularly called Correspondence. Analysis (CA). (The method can also combine continuous and categorial data for the analysis and also provide further results based on CA). The method utilizes PCA approach to reduce the dimensionality of the row-column data and offers several options to analyse the categorical data and provides vissualization of the row and column points for easy interpretation. (Author, abbr.)"Chaturvedi, A.; Carroll, J.D. – An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models (Lang.: eng). - In: J.Classif. Vol. 11. No. 2. 1994. p.155-170. Groenen, P.J.F.; Mathar, R., Heiser, W.J.. – The majorization approach to multidimensional scaling for Minkowski distances (Lang.: eng). - In: J.Classif. Vol. 12, No. 1. 1995. p.3-19. Chen, Z.; Ness, J.W.v.. – Space-conserving agglomerative algorithms (Lang.: eng). - In: J.Classif. Vol. 13, No. 1. 1996. p.157-168. Daws, J.T.. – The analysis of free-sorting data: beyond pairwise (Lang.: eng). - In: J. Classif. Vol. 13, No. 1. 1995. p.57-80. Gower, J.C.; Greenacre, M.J.. – Unfolding a symmetric matrix (Lang.: eng). - In: J.Classif. Vol. 13, No. 1. 1996. p.81-105. Mirkin, B.; Arabie, P., Hubert, L.. – Additive two-mode clustering: the error-variance approach revisited (Lang.: eng). - In: J. Classif. Vol. 12, No. 2. 1995. p.243-263. Pliner, V.. – Metric unifimensional scaling and global optimization (Lang.: eng). - In: J. Classif. Vol. 13, No. 1. 1996. p.3-18. Simantiraki, E.. – Unidimensional scaling: a linear programming approach minimizing absolute deviations (Lang.: eng). - In: J. Classif. Vol. 13, No. 1. 1996. p.19-25. Bianchini, Carlo. – Book number: uno strumento per l'organizzazione delle collezioni (Lang.: it). - Milano, IT, Editrice Bibliografica, 2017. – pp. 130. – Available at – 9788870759556. Georgel, A.; Laurent, D.. – Classification statistique et réseau de neurones formels pour la représentation de banques de données documentaires [Statistical classification and neural networks for documentary database representation] (Lang.: fre). - Paris, Université 07, 1992. – pp. 282. Doctoral Diss.Burgin, R.. – The retrieval effectiveness of five clustering algorithms as a function of indexing exhaustivity (Lang.: eng). - In: J. Amer.Soc.Inform.Sci. Vol. 46, No. 8. 1995. p.562-572.
Further items on this class as a particular theme
© ISKO 2004-2020 ; last update 2020.06.10 by CG
|