Abstract and Keywords
Automatic extraction of metadata from free text is key to digesting stored literature information, especially in dynamic and rapidly evolving fields, such as biomedicine. Besides, more and more applications heavily depend on knowledge and ontologies. Successfully recognizing or extracting terms and their relations in scientific and technical documents without human intervention is crucial to semantically structuring literature and populating ontologies. This task has been recognized as the bottleneck in exploiting fields that involve complex and dynamically changing terms, and thus has become an important research topic in Natural Language Processing. This chapter presents a brief but complete overview of automatic term recognition techniques and discusses a number of crucial practical issues. Subsequently, it focuses on evaluation, discusses available resources, and highlights a number of applications.
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