Answer selection (AS) is an essential subtask in the field of naturallanguage processing with an objective to identify the most likely answer to agiven question from a corpus containing candidate answer sentences . ASBERT is a framework built on the BERT architecture that uses Siamese and Triplet neural networks to learn an encoding function that maps a text to a fixed-size vector in an embedded space . The notion of distance between two points in this space connotes similarity in meaning between twotexts . Experimental results on the WikiQA and TrecQA datasets demonstrate that our proposed approach outperforms many state-of-the-art baseline methods . We present ASBERt, which uses

Author(s) : Olabanji Shonibare

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Coursera

Keywords : asbert - answer - triplet - question - siamese -

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