Classification of Master Data of Products and Commodities based upon Pattern Matching

For all major industries it is an important issue to classify products, parts or commodities. Classification of existing products, parts or commodities is a precondition for cost reduction thru the whole process chains, efficient stock keeping, disposability of single engines or services and factories or power stations. The problem of incompatible classification system becomes the worse that more companies want to use electronical market places. The aim for this contribution is the discussion of an approach to classify the new products in the RWE classification system via the software tool - e-proCAT [1] - based on pattern matching in strings of product descriptions and using an implementation of the Boyer-Moore-Algorithm.