By Barbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel (auth.), Jorma Laaksonen, Timo Honkela (eds.)
This e-book constitutes the refereed lawsuits of the eighth overseas Workshop on Self-Organizing Maps, WSOM 2011, held in Espoo, Finland, in June 2011. The 36 revised complete papers provided have been conscientiously reviewed and chosen from a variety of submissions. The papers are prepared in topical sections on plenaries; monetary and societal purposes; idea and technique; purposes of knowledge mining and research; language processing and rfile research; and visualization and picture processing.
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Additional info for Advances in Self-Organizing Maps: 8th International Workshop, WSOM 2011, Espoo, Finland, June 13-15, 2011. Proceedings
The numerals are clustered very compactly around the lower left corner of the SOM, and this cluster does not depend on word frequency. The conjunctions, on the other hand, have histograms scattered randomly over the area of the SOM, showing that they do not correlate with the text. The pronouns are projected into areas occupied by the other word classes. In Fig. 2 we saw the mapping of the attributive pronouns. The pronouns used as subjects or objects have histograms similar to those of the nouns, conﬁrming that it is the role of the words as sentence constituents rather than their linguistic class that is reﬂected in the contextual SOMs.
One can immediately note the concentration eﬀect for p > 2 (Figure 1(c) and 1(d)): the blank parts of the maps are the only ones where winner nodes are placed. This is a common feature to all SOMs trained with p >> 2. Concentration was less evident for p < 2; in such case, however, the advantage of using p values other than two was not as higher (with respect to the quantization error) as to justify the replacement of p = 2. 5 (c) p=5 (b) p=2 (d) p=10 Fig. 1. Distance matrix with map units size for the four best performing SOMs 36 M.
Several experiments were performed to set the μ - and c-values. 1 The Financial Benchmarking Model The financial benchmarking model was created to perform longitudinal financial performance benchmarking of international pulp and paper companies. The model Fuzzy Clustering of the SOM: Some Applications on Financial Time Series 43 consisted of seven financial ratios for the years 1995–2003, for a total of 78 pulp and paper companies. The ratios included were operating margin, return on equity, and return on total assets (profitability ratios), equity to capital and interest coverage (solvency ratios), quick ratio (liquidity ratio), and receivables turnover (efficiency ratio).
Advances in Self-Organizing Maps: 8th International Workshop, WSOM 2011, Espoo, Finland, June 13-15, 2011. Proceedings by Barbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel (auth.), Jorma Laaksonen, Timo Honkela (eds.)