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Lexical Granularity for Automatic Indexing and Means to Achieve It: The Case of Swedish MeSH®
Abstract
The identification and mapping of terminology from large repositories of life science data onto concept hierarchies constitute an important initial step for a deeper semantic exploration of unstructured textual content. Accurate and efficient mapping of this kind is likely to provide better means of enhancing indexing and retrieval of text, uncovering subtle differences, similarities and useful patterns, and hopefully new knowledge, among complex surface realisations, overlooked by shallow techniques based on various forms of lexicon look-up approaches. However, a finer-grained level of mapping between terms as they occur in natural language and domain concepts is a cumbersome enterprise that requires various levels of processing in order to make explicit relevant linguistic structures. This chapter highlights some of the challenges encountered in the process of bridging free text to controlled vocabularies and thesauri and vice versa. The author investigates how the extensive variability of lexical terms in authentic data can be efficiently projected to hierarchically structured codes, while means to increase the coverage of the underlying lexical resources are also investigated.
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