IARNN-Based Semantic-Containing Double-Level Embedding Bi-LSTM for Question-and-Answer Matching
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DOI: 10.1155/2019/6074840
Abstract: We propose a novel end-to-end approach, namely, the semantic-containing double-level embedding Bi-LSTM model (SCDE-Bi-LSTM), to solve the three key problems of Q&A matching in the Chinese medical field. In the similarity calculation of the Q&A… read more here.
Keywords: double level; level embedding; containing double; embedding lstm ... See more keywords