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HDLTex: Hierarchical Deep Learning for Text Classification

Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi, Matthew S. Gerber, Laura E. Barnes
2017 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)  
Instead we perform hierarchical classification using an approach we call Hierarchical Deep Learning for Text classification (HDLTex).  ...  HDLTex employs stacks of deep learning architectures to provide specialized understanding at each level of the document hierarchy.  ...  Fig. 2 : 2 HDLTex: Hierarchical Deep Learning for Text Classification. This is our structure of Recurrent Neural Networks (RNN) for text classification.  ... 
doi:10.1109/icmla.2017.0-134 dblp:conf/icmla/KowsariBHMGB17 fatcat:rj6nx4cwa5bfndeqof7fiwqtze

A Hierarchical Neural Attention-based Text Classifier

Koustuv Sinha, Yue Dong, Jackie Chi Kit Cheung, Derek Ruths
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
Deep neural networks have been displaying superior performance over traditional supervised classifiers in text classification.  ...  In this work, we use external knowledge in the form of topic category taxonomies to aide the classification by introducing a deep hierarchical neural attention-based classifier.  ...  We would also express our appreciation to our sponsors, Pierre Arbour Foundation and FRQNT for supporting Koustuv Sinha and NSERC for supporting Yue Dong for this research. 8 We use the same visualization  ... 
doi:10.18653/v1/d18-1094 dblp:conf/emnlp/SinhaDCR18 fatcat:yzkihgzhvndazal2ooiojavbgy

Joint Embedding of Words and Category Labels for Hierarchical Multi-label Text Classification [article]

Jingpeng Zhao, Yinglong Ma
2020 arXiv   pre-print
In this paper, We propose a joint embedding of text and parent category based on hierarchical fine-tuning ordered neurons LSTM (HFT-ONLSTM) for HTC.  ...  At present, hierarchical text classification (HTC) has received extensive attention and has broad application prospects.  ...  Hierarchical classification based on deep learning has become the mainstream. Kowsari et al. proposed a local hierarchical classification method called HDLTex Fig. 1 . 1 Fig. 1.  ... 
arXiv:2004.02555v3 fatcat:5sxacrn4yradddmrldf6il6pii

HFT-ONLSTM: Hierarchical and Fine-Tuning Multi-label Text Classification [article]

Pengfei Gao, Jingpeng Zhao, Yinglong Ma, Ahmad Tanvir, Beihong Jin
2022 arXiv   pre-print
First, we present a novel approach to learning the joint embeddings based on parent category labels and textual data for accurately capturing the joint features of both category labels and texts.  ...  Second, a fine tuning technique is adopted for training parameters such that the text classification results in the upper level should contribute to the classification in the lower one.  ...  HFT-ONLSTM: Hierarchical and Fine-Tuning Multi-label Text Classification 27 They have no conflicts of interest to declare that are relevant to the content of this article.  ... 
arXiv:2204.08115v1 fatcat:drutc57uvbdfnm3bpun6o53tx4

Bitcoin Value and Sentiment Expressed in Tweets

Bernhard Preisler, Margot Mieskes, Christoph Becker
2019 Swiss Text Analytics Conference  
As Bitcoin and other cryptocurrencies are a playground for technically interested people, it might be worthwhile to look into other communication channels, such as Social Media to find clues for the development  ...  In this work, we present a data set of Tweets covering almost one year, which we annotated for Sentiment.  ...  Acknowledgments This work was supported by the research center for Applied Computer Science (FZAI) and the Faculty for Mathematics and Natural Sciences, University of Applied Sciences Darmstadt.  ... 
dblp:conf/swisstext/PreislerMB19 fatcat:clm72e3oingb7kjjsvxxtxrasm

RMDL

Kamran Kowsari, Mojtaba Heidarysafa, Donald E. Brown, Kiana Jafari Meimandi, Laura E. Barnes
2018 Proceedings of the 2nd International Conference on Information System and Data Mining - ICISDM '18  
This paper introduces Random Multimodel Deep Learning (RMDL): a new ensemble, deep learning approach for classification.  ...  This paper describes RMDL and shows test results for image and text data including MNIST, CIFAR-10, WOS, Reuters, IMDB, and 20newsgroup.  ...  [23] introduced hierarchical deep learning for text classification (HDLTex) which is a combination of all deep learning techniques in a hierarchical structure for document classification has improved  ... 
doi:10.1145/3206098.3206111 dblp:conf/icisdm/KowsariHBMB18 fatcat:lzyx7ze67vgu5lv2jbguion544

Comprehensive evaluation of Hybrid RNN Model embedded with LSTM and GRU Layers for Text Classification

Sunagar*, Pramod, Kanavalli**, Anita
2021 Zenodo  
Text classification has moved towards neural networks from the conventional machine learning algorithms to address the intricacies embedded in the process of classification.  ...  Abstract— Though text classification has gained great importance over a decade, there are umpteen number of methods developed to address the challenges pertaining to text classification.  ...  The authors discussed a deep learning strategy called as HDLTex in this paper, which integrates various deep learning algorithms to create hierarchical classifications [23] .  ... 
doi:10.5281/zenodo.5804112 fatcat:jg2t5ampxrd7biymqd6qqmqmya

Gender Detection on Social Networks using Ensemble Deep Learning [article]

Kamran Kowsari, Mojtaba Heidarysafa, Tolu Odukoya, Philip Potter, Laura E. Barnes, Donald E. Brown
2020 arXiv   pre-print
This paper addresses this problem in the context of gender detection through ensemble classification that employs multi-model deep learning architectures to generate specialized understanding from different  ...  Analyzing the ever-increasing volume of posts on social media sites such as Facebook and Twitter requires improved information processing methods for profiling authorship.  ...  Kowsari et. al. in 2017 [14] introduced hierarchical deep learning for text classification (HDLTex) to the field.  ... 
arXiv:2004.06518v3 fatcat:s6dwyv6w7nbqvicrr6oezbrwxi

NeuralClassifier: An Open-source Neural Hierarchical Multi-label Text Classification Toolkit

Liqun Liu, Funan Mu, Pengyu Li, Xin Mu, Jing Tang, Xingsheng Ai, Ran Fu, Lifeng Wang, Xing Zhou
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations  
In this paper, we introduce NeuralClassifier, a toolkit for neural hierarchical multi-label text classification.  ...  NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios.  ...  On the other hand, there is limited choice for neural hierarchical multi-label text classification toolkits.  ... 
doi:10.18653/v1/p19-3015 dblp:conf/acl/LiuMLMTAFWZ19 fatcat:7vcqanwnovcupni7ii25rayov4

A Hybrid RNN based Deep Learning Approach for Text Classification

Pramod Sunagar, Anita Kanavalli
2022 International Journal of Advanced Computer Science and Applications  
To handle the complexities involved in the text classification process, the focus has shifted away from traditional machine learning methods and toward neural networks.  ...  Despite the fact that text classification has grown in relevance over the last decade, there are a plethora of approaches that have been created to meet the difficulties related with text classification  ...  The authors discussed a deep learning strategy called HDLTex, which integrates various deep learning algorithms to create hierarchical classifications [23] .  ... 
doi:10.14569/ijacsa.2022.0130636 fatcat:b76g6zjip5ejbgb3vdu36kilee

Text Classification Algorithms: A Survey

Kowsari, Jafari Meimandi, Heidarysafa, Mendu, Barnes, Brown
2019 Information  
However, finding suitablestructures, architectures, and techniques for text classification is a challenge for researchers.  ...  In thispaper, a brief overview of text classification algorithms is discussed.  ...  Gerber for his feedback and comments. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/info10040150 fatcat:qfmjtzsaoreahdwdwlfhymjtru

Hierarchy Decoder is All You Need To Text Classification [article]

SangHun Im, Gibaeg Kim, Heung-Seon Oh, Seongung Jo, Donghwan Kim
2021 arXiv   pre-print
Hierarchical text classification (HTC) to a taxonomy is essential for various real applications butchallenging since HTC models often need to process a large volume of data that are severelyimbalanced  ...  In addition, itcan be applied to both single- and multi-label classification with a minor modification.  ...  Related Works Previous studies have used deep learning for text classification (TC).  ... 
arXiv:2111.11104v1 fatcat:ow4zdzjbrjerbgraqducmkmgxy

Hierarchical Text Classification of Urdu News using Deep Neural Network [article]

Taimoor Ahmed Javed, Waseem Shahzad, Umair Arshad
2021 arXiv   pre-print
This paper proposes a deep learning model for hierarchical text classification of news in Urdu language - consisting of 51,325 sentences from 8 online news websites belonging to the following genres: Sports  ...  The result shows that our proposed method is very effective for hierarchical text classification and it outperforms baseline methods significantly and also achieved good results as compare to deep neural  ...  This paper [18] proposed a new approach for hierarchical classification of text which is named as Hierarchical Deep learning for text classification.  ... 
arXiv:2107.03141v1 fatcat:kxrtu6i7ongzrfcotihjvqvtdu

Towards Robust Text Classification with Semantics-Aware Recurrent Neural Architecture

Blaž Škrlj, Jan Kralj, Nada Lavrač, Senja Pollak
2019 Machine Learning and Knowledge Extraction  
Deep neural networks are becoming ubiquitous in text mining and natural language processing, but semantic resources, such as taxonomies and ontologies, are yet to be fully exploited in a deep learning  ...  This paper presents an efficient semantic text mining approach, which converts semantic information related to a given set of documents into a set of novel features that are used for learning.  ...  Acknowledgments: The GPU used for this research was donated by the NVIDIA Corporation. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/make1020034 fatcat:o6bjp46cljdj3kng2kxsfvvzei

Text Mining: Classification of Text Documents using Granular Hybrid Classification Technique

Shiva Prasad KM, Dr.T Hanumantha Reddy
2019 International Journal of Research in Advent Technology  
Imagine we want to classify a product code from a large corpus based on the text written by a user.  ...  Maintaining and procuring the data is busy task for all the users who are willing to access the information in line with the requirements, however, the digital knowledge that's unbroken throughout this  ...  Instead we tend to perform ranked classification using an approach we call Hierarchical Deep Learning for Text classification (HDLTex).  ... 
doi:10.32622/ijrat.76201910 fatcat:sjpaeob3bzf3xmq4fi27sfp4n4
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