Named Entity Recognition Model Based on the Fusion of Word Vectors and Category Vectors

Named Entity Recognition Model Based on the Fusion of Word Vectors and Category Vectors

Named entity recognition (NER) in deep learning mode heavily relies on the processing and analysis of text vectors. This paper introduces an NER model based on deep learning techniques, emphasizing the fusion of word vectors and category vectors to enhance text processing and analysis capabilities....

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Bibliographic Details
Main Authors: Yang Zhou, Haoyang Zeng, Wei Zhang, Yuguang Zhang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
BERT
named entity recognition (NER)
bi-directional long short term memory networks (BiLSTM)
category vectors
word vectors
Online Access:https://ieeexplore.ieee.org/document/10806666/
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https://ieeexplore.ieee.org/document/10806666/

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