ARTÍCULO
TITULO

Topological Data Analysis Helps to Improve Accuracy of Deep Learning Models for Fake News Detection Trained on Very Small Training Sets

Ran Deng and Fedor Duzhin    

Resumen

Topological data analysis has recently found applications in various areas of science, such as computer vision and understanding of protein folding. However, applications of topological data analysis to natural language processing remain under-researched. This study applies topological data analysis to a particular natural language processing task: fake news detection. We have found that deep learning models are more accurate in this task than topological data analysis. However, assembling a deep learning model with topological data analysis significantly improves the model?s accuracy if the available training set is very small.

 Artículos similares

       
 
Luigi Calabrese, Massimiliano Galeano and Edoardo Proverbio    
In this paper, time/frequency domain data processing was proposed to analyse the EN signal recorded during stress corrosion cracking on precipitation-hardening martensitic stainless steel in a chloride environment. Continuous Wavelet Transform, albeit wi... ver más

 
Younes Hamdani, Guohui Xiao, Linfang Ding and Diego Calvanese    
The integration of the raster data cube alongside another form of geospatial data (e.g., vector data) raises considerable challenges when it comes to managing and representing it using knowledge graphs. Such integration can play an invaluable role in han... ver más

 
Jiaming Ye, Defu Che, Baodong Ma, Quan Liu, Kehan Qiu and Xiangxiang Shang    
Existing approaches for the 3D modeling of tunnels suffer from several problems, such as highly difficult data acquisition, redundancy of model data, large computational burden, and the inability of the resulting models to be monolithic. Therefore, solut... ver más

 
Jianfei Wang and Wen Cao    
In the era of big data, a significant volume of spatiotemporal data exists in a multiscale format, describing diverse phenomena in the objective world across different spatial and temporal scales. While existing methods focus on analyzing the features an... ver más

 
Zhuhua Liao, Haokai Huang, Yijiang Zhao, Yizhi Liu and Guoqiang Zhang    
Urban planning and function layout have important implications for the journeys of a large percentage of commuters, which often make up the majority of daily traffic in many cities. Therefore, the analysis and forecast of traffic flow among urban functio... ver más