Semantic Textual Similarity with Siamese Neural Networks
Tharindu Ranasinghe, Constantin Orǎsan, Ruslan Mitkov · 2019
Calculating 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.