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Towards a Universal Method for Measuring Semantic Textual Similarity

Semantic textual similarity (STS) measures the degree to which two texts share the same meaning. In Natural Language Processing, STS touches many different aspects, from thesaurus generation to machine translation. However, methods for measuring STS have often been developed only for very specific types of texts, such as for comparing two words or for comparing paragraphs. This disjoint approach creates the predicament where different similarity methods have to be used depending on the type of text being compared.