Title :
Ontology-based classification of unstructured information
Author :
Burger, Stefan ; Stieger, Bernd
Author_Institution :
Dept. of Comput. Sci., Eastern Michigan Univ., Ypsilanti, MI, USA
Abstract :
The area of knowledge management (KM) has been addressed with a considerable amount of research in order to develop concepts and technologies for the retrieval of information and knowledge out of a set of heterogeneous data sources. Especially when we deal with files which contain unstructured information, i.e. documents, it is still a huge challenge to classify them automatically into certain domain-dependant categories. Therefore, this paper describes an application and the underlying concepts which are used for a classification based on the available metadata of files, whereas the classification categories can be found in form of ontology classes. This paper discusses experiences and challenges during the implementation with special regard to ontology-based classification algorithms, the underlying framework as well as the importance metadata quality.
Keywords :
classification; information retrieval; knowledge management; meta data; ontologies (artificial intelligence); text analysis; document handling; heterogeneous data sources; information retrieval; knowledge management; metadata; ontology-based classification; unstructured information; Business; Data mining; Indexes; Ontologies; Power supplies; Resource description framework; Semantics;
Conference_Titel :
Digital Information Management (ICDIM), 2010 Fifth International Conference on
Conference_Location :
Thunder Bay, ON
Print_ISBN :
978-1-4244-7572-8
DOI :
10.1109/ICDIM.2010.5664634