Semantic Enhancement Engine: A Modular Document Enhancement Platform for Semantic Applications over Heterogeneous Content

Brian Hammond, Amit Sheth, Krzysztof Kochut · 2002

Abstract. Traditionally, automatic classification and metadata extraction have been performed in isolation, usually on unformatted text. SCORE Enhancement Engine (SEE) is a component of a Semantic Web technology called the Semantic Content Organization and Retrieval Engine (SCORE). SEE takes the next natural steps by supporting heterogeneous content (not only unformatted text), as well as following up automatic classification with extraction of contextually relevant, domain-specific (i.e., semantic) metadata. Extraction of semantic metadata not only includes identification of relevant entities but also relationships within the context of relevant ontology. This paper describes SEE's architecture, which provides a common API for heterogeneous document processing, with discrete, reusable and highly configurable modular components. This results in exceptional flexibility, extensibility and performance. Referred to as SEE modules (SEEMs), which are divided along functional lines, these processors perform one of the following roles: restriction (determine the segments of the input text to operate upon); enhancement (discover textual features of semantic interest); filtering (augment, remove or supplement the features recognized); or

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