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Knowledge organization systems (KOS), like thesauri and other controlledvocabularies, are used to provide subject access to information systems acrossthe web. Due to the heterogeneity of these systems, mapping betweenvocabularies becomes crucial for retrieving relevant information. However,mapping thesauri is a laborious task, and thus big efforts are being made toautomate the mapping process. This paper examines two mapping approachesinvolving the agricultural thesaurus AGROVOC, one machine-created and one humancreated. We are addressing the basic question "What are the pros and cons ofhuman and automatic mapping and how can they complement each other?" Bypointing out the difficulties in specific cases or groups of cases and groupingthe sample into simple and difficult types of mappings, we show the limitationsof current automatic methods and come up with some basic recommendations onwhat approach to use when.

Comparing human and automatic thesaurus mapping approaches in the agricultural domain