Incorporating Label Co-Occurrence Into Neural Network-Based Models for Multi-Label Text Classification

Incorporating Label Co-Occurrence Into Neural Network-Based Models for Multi-Label Text Classification

Multi-label text classification (MLTC) addresses a fundamental problem in natural language processing, which assigns multiple relevant labels to each document. In recent years, Neural Network-based models (NN models) for MLTC have attracted much attention. In addition, NN models achieve favorable pe...

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Bibliographic Details
Main Authors: Jiaqi Yao, Keren Wang, Jikun Yan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Multi-label text classification
label co-occurrence
initialization
neural network
class embedding
Online Access:https://ieeexplore.ieee.org/document/8936450/

Internet

https://ieeexplore.ieee.org/document/8936450/

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