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SemTag and Seeker: Bootstrapping the Semantic Web Via Automated Semantic Annotation

Overview This paper describes Seeker, a platform for large-scale text analytics, and SemTag, an application written on the platform to perform automated semantic tagging of large corpora. The paper describes the Seeker platform, discusses the architecture of the SemTag application, describes a new disambiguation algorithm specialized to support ontological disambiguation of large-scale data, evaluates the algorithm, and presents the final results with information about acquiring and making use of the semantic tags. This paper also argues that automated large scale semantic tagging of ambiguous content can bootstrap and accelerate the creation of the semantic web.

Further White Paper Details
Publisher	ACM	File Format	HTML
Date Published	May 2003	Downloads	13
Format	White Papers
Topics	Web Services, Search Strategies, Data Mining / Analysis

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