Melike Sah and Vincent Wade, Automatic Metadata Extraction from Multilingual Enterprise Content, ACM International Conference on Information and Knowledge Management (CIKM 2010), Toronto, Canada, 2010, 1665 - 1668
Enterprises provide professionally authored content about their products/services in different languages for use in web sites and
customer care. For customer care, personalization/personalized information delivery is becoming important since it re-encourages users to return to the service provider. Personalization usually requires both contextual and descriptive metadata. But current metadata authored by content developers is usually quite simple. In this paper, we introduce an automatic metadata extraction framework, which can extract multilingual metadata from the enterprise content, for a personalized information retrieval system. We introduce two new ontologies for metadata creation and a novel semi-automatic topic vocabulary extraction
algorithm. We demonstrate and evaluate our approach on the English and German Symantec Norton 360 technical content. Evaluations indicate that the proposed approach produces rich and high quality metadata for a personalized information retrieval system.
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