Journal ArticleDOI
A Survey on Text Classification: From Traditional to Deep Learning
TLDR
A taxonomy for text classification according to the text involved and the models used for feature extraction and classification is created, dealing with both the technical developments and benchmark datasets that support tests of predictions.Abstract:
Text classification is the most fundamental and essential task in natural language processing. The last decade has seen a surge of research in this area due to the unprecedented success of deep learning. Numerous methods, datasets, and evaluation metrics have been proposed in the literature, raising the need for a comprehensive and updated survey. This paper fills the gap by reviewing the state-of-the-art approaches from 1961 to 2021, focusing on models from traditional models to deep learning. We create a taxonomy for text classification according to the text involved and the models used for feature extraction and classification. We then discuss each of these categories in detail, dealing with both the technical developments and benchmark datasets that support tests of predictions. A comprehensive comparison between different techniques, as well as identifying the pros and cons of various evaluation metrics are also provided in this survey. Finally, we conclude by summarizing key implications, future research directions, and the challenges facing the research area.read more
Citations
More filters
Journal ArticleDOI
BERT Models for Arabic Text Classification: A Systematic Review
TL;DR: This review synthesizes the different Arabic BERT models that have been applied to text classification, investigates the differences between them and compares their performance, and examines how effective they are compared to the original English Bert models.
Journal ArticleDOI
Multi-modal spatio-temporal meteorological forecasting with deep neural network
Xinbang Zhang,Qizhao Jin,Tingzhao Yu,Shiming Xiang,Qiuming Kuang,Veronique Prinet,Chunhong Pan +6 more
TL;DR: Wang et al. as discussed by the authors proposed a deep learning framework to model the dynamics of multi-modal meteorological data along spatial and temporal dimensions, where a convolution-based network was developed to extract the spatial context of multidimensional meteorological datasets.
Journal ArticleDOI
The power of talk: Exploring the effects of streamers' linguistic styles on sales performance in B2B livestreaming commerce
TL;DR: In this paper , the authors examined the impact of three speech acts (i.e., assertive, expressive, and directive speech acts) on sales performance in online B2B marketplaces by conducting a streamer-level analysis.
Journal ArticleDOI
Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets
Fabian Karl,Ansgar Scherp +1 more
TL;DR: In this article , the performance of a variety of short text classifiers as well as the top performing traditional text classifier was examined. And the effects on two new real-world short text datasets in an effort to address the issue of becoming overly dependent on benchmark datasets with a limited number of characteristics.
Journal Article
Analyzing the Effects of Annotator Gender across NLP Tasks
Laura Jean Press Biester,Vanita Sharma,Ashkan Kazemi,Naihao Deng,Steven R. Wilson,Rada Mihalcea +5 more
TL;DR: This work hypothesizes that gender may correlate with differences in annotations for a number of NLP benchmarks, including those that are fairly subjective and those typically considered to be objective, and develops a robust framework to test for differences in annotation across genders.
References
More filters
Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Journal ArticleDOI
Long short-term memory
TL;DR: A novel, efficient, gradient based method called long short-term memory (LSTM) is introduced, which can learn to bridge minimal time lags in excess of 1000 discrete-time steps by enforcing constant error flow through constant error carousels within special units.
Proceedings Article
Attention is All you Need
Ashish Vaswani,Noam Shazeer,Niki Parmar,Jakob Uszkoreit,Llion Jones,Aidan N. Gomez,Lukasz Kaiser,Illia Polosukhin +7 more
TL;DR: This paper proposed a simple network architecture based solely on an attention mechanism, dispensing with recurrence and convolutions entirely and achieved state-of-the-art performance on English-to-French translation.
Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.