@inproceedings{c13b728a729348a59ad464f079606ff6,
title = "Multi-label Text Classification with Deep Neural Networks",
abstract = "Text classification is a foundational task in natural language processing (NLP). Traditional methods rely heavily on human-designed features, while deep learning models based on neural networks can automatically capture contextual information. We explore and introduce various neural network architectures to extract information and key components in texts. An extensive set of experiments and comparisons on accuracy, speed, memory-consumption are conducted. Methods based on the proposed models won the first place in the Zhihu Machine Learning Challenge 2017. The code has been made publicly available.",
keywords = "Deep Learning, Multi-label Classification, Natural Language Processing, Neural Network",
author = "Yun Chen and Bo Xiao and Zhiqing Lin and Cheng Dai and Zuochao Li and Liping Yan",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 ; Conference date: 22-08-2018 Through 24-08-2018",
year = "2018",
month = nov,
day = "6",
doi = "10.1109/ICNIDC.2018.8525817",
language = "English",
series = "Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "409--413",
booktitle = "Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018",
address = "United States",
}