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AbstractCalculating the Semantic Textual Similarity (STS) is an important research area in natural language processing which plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction. This paper evaluates Siamese recurrent architectures, a special type of neural networks, which are used here to measure STS. Several variants of the architecture are compared with existing methods
CitationOrasan, C., Mitkov, R. and Ranasinghe, T. (2019) Semantic textual similarity with siamese neural networks, RANLP 2019, 2nd-4th September 2019, Varna, Bulgaria.
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