Title: Measuring Semantic Similarity Between Sentences Using A Siamese Neural Network
Abstract: The task of measure semantic redundancy between sentences demands a thorough interpretation from the reader because phrase meaning may be ambiguous. Detecting semantic similarity is a difficult problem because natural language, besides ambiguity, offers almost infinite possibilities to express the same idea. This paper adapts a siamese neural network architecture trained to measure the semantic similarity between two sentences through metric learning. The resulting solution should help in writing more efficient and informative text.
Publication Year: 2018
Publication Date: 2018-07-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 20
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