CHARM: An Improved Method for Chinese Precoding and Character-Level Embedding
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3112190
Abstract: The numerical transformation of text is a key step in natural language processing tasks, among which the word embedding model is the most representative. However, the word embedding model is insufficient in representing unregistered and… read more here.
Keywords: charm; level; character level; model ... See more keywords
IARNN-Based Semantic-Containing Double-Level Embedding Bi-LSTM for Question-and-Answer Matching
Sign Up to like & getrecommendations! Published in 2019 at "Computational Intelligence and Neuroscience"
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