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Статья

Corpus-Based Text Retrieval and Adaptation for Learning System

The algorithm to adapt lexical complexity in the news article which can be used as materials for learning language presented in the paper. We consider words substitution retrieval according to wordnet-based and corpus-based semantic relatedness. Two corpus-based similarity measures empirically tested: Vector Space Model and Distributional Semantic Model. This language processing algorithm has created as a client-server application. It retrieves appropriate text from Web-resource. Next it performs adaptation procedure.