Using domain knowledge for ontology-guided entity extraction from noisy, unstructured text data
Sergey Bratus, Anna Rumshisky, Rajendra Magar, Paul Thompson · 2009
Domain-specific knowledge is often recorded by experts in the form of unstructured text. For example, in the medical domain, clinical notes from electronic health records contain a wealth of information. Similar practices are found in other domains. The challenge we discuss in this paper is how to identify and extract part names from technicians repair notes, a noisy unstructured text data source from General Motors' archives of solved vehicle repair problems, with the goal to develop a robust and dynamic reasoning system to be used as a repair adviser by service technicians.