Comparing Human and Automatic Thesaurus Mapping Approaches in the Agricultural Domain

Boris Lauser, Gudrun Johannsen, Caterina Caracciolo, Willem Robert van Hage, Johannes Keizer, Philipp Mayr


Knowledge organization systems (KOS), like thesauri and other
controlled vocabularies, are used to provide subject access to information systems
across the web. Due to the heterogeneity of these systems, mapping between
vocabularies becomes crucial for retrieving relevant information. However, mapping
thesauri is a laborious task, and thus big efforts are being made to automate the
mapping process. This paper examines two mapping approaches involving the
agricultural thesaurus AGROVOC, one machine-created and one human created. We are
addressing the basic question ‘What are the pros and cons of human and automatic
mapping and how can they complement each other?’ By pointing out the difficulties in
specific cases or groups of cases and grouping the sample into rather simple and
rather difficult types of mappings, we show the limitations of current automatic
methods and come up with some basic recommendations on what approach to use when.

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