Context-specific Consistencies in Information Extraction
Rule-based and Probabilistic Approaches
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Beschreibung
Information extraction is widely used to identify well-defined entities and relations in unstructured data. Interesting entities are often consistently structured within a certain context, especially in semi-structured texts. However, their actual composition varies and is possibly inconsistent among different contexts. Information extraction models stay behind their potential and return inferior
results if they do not consider these consistencies during processing. This work presents a selection of practical and novel approaches for exploiting these context-specific consistencies in information extraction tasks. The approaches direct their attention not only to one technique, but are based on handcrafted rules as well as probabilistic models.
Autor*in
Peter Klügl
Geboren 1981 in Ingolstadt
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