Semantic Web Technologies for Classification and Indexing of E-government Archive
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Abstract
Semantic web Meta data and natural language
processing technologies can be combined to produce systems
that working more efficiently for classification and retrieval
of documents. The main aim of this Paper is applying
semantic web technologies and tools for indexing,
classifying, and retrieving Arabic content documents within
E-government archive by using semantic web annotation
technology and natural language processing (NLP).
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