Semantic metadata extraction using xemanticA analysis

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2010

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Abstract

Identifying Metadata and understanding the semantics of them is vitally important and advantageous analyzing, managing and utilizing information. This paper suggests a new technique which we call XemanticA Analysis that is derived based on Latent Semantic Analysis (LSA). With this new technique phrases, sentences or documents are evaluated with respect to their context and the system needs an initial, training with respect to some known data. The technique which is proposed here has also been implemented and in this paper we introduce some of the important facts on the accuracy results and the outcomes of this technique and its implementation This is a technique which can be used immensely in applications and there can he many extensions and enhancements that can be performed over the outcomes of this method.

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Semantics, XemanticA Analysis, Metadata Extraction, Content Matrix (CM),, Singular la Decomposition (SI D), Talent Semantic Analysis (LAS)

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