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When insurance companies calculate compensation for products no longer on the market, they need to identify an equal product for val- uation. Subjectively matching products poses a unique challenge with a many-to-many pairing, which is currently handled by an algorithm that requires day-to-day maintenance. This thesis investigates current methodologies and tools and presents unique machine learnin
