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By Iavor Marangozov

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Extra resources for Characteristics of the International Joint Ventures in Bulgaria (European Business Review, Vol. 17, No. 3, pp. 242-262, 2005)

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Number-letter combinations such as “100g” are separated, as are camel-cased 24 M. van Assem et al. tokens (“StartTime”). Basic classification of tokens into numbers, punctuation, and words is performed. Punctuation tokens that may represent multiplication (period, stars, dots), and division (slash) are also typed. g. mean, total, expected, estimated). g. g. g. “C” for ◦ C, s-1 vs. sˆ-1 vs. 1/s for reciprocal units, sˆ2 vs. s2 for exponentiated units). Because these can be generated systematically this is easier than adding them to the ontology.

G. “C” for ◦ C, s-1 vs. sˆ-1 vs. 1/s for reciprocal units, sˆ2 vs. s2 for exponentiated units). Because these can be generated systematically this is easier than adding them to the ontology. Matching starts by comparing the input to full names of quantities and units, including confused with and colloquial abbreviations. The match with the highest score above a threshold is selected. We have used a string distance metric to overcome spelling mistakes, called Jaro-Winkler-TFIDF [3]. g. “f”, “km”, “s”).

Magnetic field intensity”, “luminous intensity”). g. weight and mass). Our ontology records the concepts and their definitions as they are prescribed in standards, but for automated annotation it is useful to know which terms people use to denote these concepts. This dichotomy is well-known in the vocabulary world, and reflected in the SKOS standard through the skos:hiddenLabel property4 . It is used to record labels not meant for display but useful in searching. We introduce a property confused with (subproperty of skos:hiddenLabel).

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