@sebastian.furth

Towards the Semantification of Technical Documents

, and . FGIR'13: Proceedings of German Workshop of Information Retrieval (at LWA'2013), (2013)

Abstract

In the domain of engineering large corpora of technical documents are commonly created and used. Applications such as semantic search offer advantages in accessing those documents, but require them to be semantically annotated. Annotating these corpora manually is in most cases not feasible. In recent years a lot of machine learning methods have proved their ability to annotate documents automatically. The down-side of these methods is their need for training data. We present a holistic approach for the semantification of technical documents without training data. The approach tackles different challenges such as terminology extraction, semantic annotation, and reviewing. Our approach has been successfully applied to the technical documents corpora of two German machine builders

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