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Deep Learning Based on Hierarchical Self-Attention for Finance Distress Prediction Incorporating Text

Sumei Ruan, Xusheng Sun, Ruanxingchen Yao, Wei Li, Nian Zhang
2021 Computational Intelligence and Neuroscience  
To detect comprehensive clues and provide more accurate forecasting in the early stage of financial distress, in addition to financial indicators, digitalization of lengthy but indispensable textual disclosure  ...  prediction, which is suitable for extracting effective parts of the large-scale text.  ...  Hajek and Henriques [5] deal with counted sentiment words with a random subspace method as an additional feature for financial distress forecasting.  ... 
doi:10.1155/2021/1165296 pmid:34925482 pmcid:PMC8683239 fatcat:d2qsd7df3reozib4k5eafqu4ua

Comprehensive review of text-mining applications in finance

Aaryan Gupta, Vinya Dengre, Hamza Abubakar Kheruwala, Manan Shah
2020 Financial Innovation  
It also analyses the existing literature on text mining in financial applications and provides a summary of some recent studies.  ...  Finally, the paper briefly discusses various text-mining methods being applied in the financial domain, the challenges faced in these applications, and the future scope of text mining in finance.  ...  Acknowledgements The authors are grateful to Nirma University and Department of Chemical Engineering, School of Technology, Pandit Deendayal Petroleum University for the permission to publish this research  ... 
doi:10.1186/s40854-020-00205-1 fatcat:c4jckxwrhfadtnalyz24trla3i

Applications of deep learning in stock market prediction: recent progress [article]

Weiwei Jiang
2020 arXiv   pre-print
Hence, our motivation for this survey is to give a latest review of recent works on deep learning models for stock market prediction.  ...  Lately, deep learning models have been introduced as new frontiers for this topic and the rapid development is too fast to catch up.  ...  Li et al. (2019b) formulates a sentiment-ARMA model to incorporate the news articles as hidden information and designs a LSTM-based DNN, which consists of three components, namely, LSTM, VADER model and  ... 
arXiv:2003.01859v1 fatcat:rdwsi5xpozfyjeg7oatfzwbg7a

Business Failure Prediction Based on a Cost-Sensitive Extreme Gradient Boosting Machine

Yao Zou, Changchun Gao, Han Gao
2022 IEEE Access  
Besides, to tackle the second issue, we explore the intrinsic interpretability of the proposed method by visualizing the feature importance and incorporating a partial dependence plot technique to locally  ...  However, the highly imbalanced class distribution of financial risk data and the inexplainable of most machine learning-based early distress warning models limit their commercial application.  ...  an ensemble strategy to extract sentiment and textual information for business failure prediction.  ... 
doi:10.1109/access.2022.3168857 fatcat:vvuxpdyiy5c6bc6efj5r64g36e

Machine Learning in Disaster Management: Recent Developments in Methods and Applications

Vasileios Linardos, Maria Drakaki, Panagiotis Tzionas, Yannis L. Karnavas
2022 Machine Learning and Knowledge Extraction  
Furthermore, some recently developed ML and DL applications for disaster management have been analyzed. A discussion of the findings is provided as well as directions for further research.  ...  This paper aims to provide an overview of the research studies, presented since 2017, focusing on ML and DL developed methods for disaster management.  ...  The developed method was based on NBT and random subspace (RS) ensemble, achieving an AUC value of landslide prediction equal to 0.886.  ... 
doi:10.3390/make4020020 fatcat:wcdrh23k5ja6tdqlyhl7erobey

COVID-19 Modeling: A Review [article]

Longbing Cao, Qing Liu
2021 arXiv   pre-print
It constructs a research landscape of COVID-19 modeling tasks and methods, and further categorizes, summarizes, compares and discusses the related methods and progress of modeling COVID-19 epidemic transmission  ...  This paper provides a comprehensive review of the challenges, tasks, methods, progress, gaps and opportunities in relation to modeling COVID-19 problems, data and objectives.  ...  We thank Wenfeng Hou, Siyuan Ren, Yawen Zheng, Qinfeng Wang and Yang Yang for their assistance in the literature collection.  ... 
arXiv:2104.12556v3 fatcat:pj2bketcrveafbjf2m7tx3odxy

COVID-19 Modeling: A Review [article]

Longbing Cao, Qing Liu
2022 medRxiv   pre-print
Such questions involve a wide body of knowledge and literature, unclear but important for the present and future health crisis quantification.  ...  particular shallow and deep machine learning, simulation modeling, social science methods and hybrid modeling have addressed the COVID-19 challenges and what gaps and directions exist for better futures  ...  We thank Wenfeng Hou, Siyuan Ren, Yawen Zheng, Qinfeng Wang and Yang Yang for their assistance in the literature collection.  ... 
doi:10.1101/2022.08.22.22279022 fatcat:qwj3bp6sa5dbrbwxk4qekjpgtq

ijair-volume-6-issue-1-vii-january-march-2019 -HINDUSTAN BOOK.pdf

V. Thamilarasi
2022 figshare.com  
This paper experiments various basic image segmentation techniques for Lung Chest X-Ray images  ...  Linear Regressions are used to predict the probability of an event, financial predictions, finding the cost estimation for software products, helps in organizing the structure of an organization in financial  ...  PUT creates a new resource which can be then deleted by using DELETE method. GET method retrieves the current state of a resource.POST method transfers a new state onto a resource.  ... 
doi:10.6084/m9.figshare.20217722.v1 fatcat:l74ihuqhcvdtjomod3zdwzfniu

Social media mental health analysis framework through applied computational approaches

Xuetong Chen
2020
However, mental disorders are difficult to diagnose and monitor through traditional methods, which heavily rely on interviews, questionnaires and surveys, resulting in high under-diagnosis and under-treatment  ...  The majority of work is developed on ad hoc datasets and lacks a systematic research pipeline. [Continues.]  ...  Features generated from a new data instance can be compared against what the prediction model learned to provide explanations on the prediction outcome of the new instance, thus provide relevant information  ... 
doi:10.26174/thesis.lboro.11794272.v1 fatcat:mvliny55kjbntoizv2eezdvsra

Automated Mental Disorders Assessment Using Machine Learning

Niloufar Abaei Koupaei, University, My
2021
The main objective of this thesis is to investigate, develop, and propose automated methods for mental disorder detection.  ...  Although the symptoms for different mental disorders vary, they generally are characterized by a combination of abnormal behaviours, thoughts, and emotions.  ...  We presented a possible vision for such system in Chapter 1.  ... 
doi:10.20381/ruor-27231 fatcat:pw6rcqdk2femrmfa2w5zktb6si

Perspectives: modes of viewing and knowing in nineteenth-century England

2010 ChoiceReviews  
The victorians institute, the MLa, The Society for Textual Studies, and the north american victorian Studies association offered valuable venues to present material on word and image to specialized audiences  ...  Shires_Final for Print.indb 11 6/22/2009 3:43:09 PM xii / Ac k n ow l e d g m e n t s nothing to do with the book; he wisely kept his perspective focused on his social life and his own intellectual and  ...  For combination printing inaugurated a new handling of photographic subject, a new language of printing, a new responsibility for the observer to read parts, and a new way of observing parts and the whole  ... 
doi:10.5860/choice.47-3032 fatcat:qvxkbehaovhm3gp4lr76oskygy

CFE-CMStatistics 2016 PROGRAMME AND ABSTRACTS 10th International Conference on CMStatistics 2016 Programme Committee

Angela Blanco-Fernandez, Gil Gonzalez-Rodriguez, Ana Colubi, Stella Hadjiantoni, M Dolores Jimenez-Gamero, Erricos Kontoghiorghes, George Loizou, Herman Van, Dijk, Peter Boswijk, Jianqing Fang, Alain Hecq (+123 others)
unpublished
We show how textual analysis can be used to nowcast economic sentiment and that these nowcasts are useful for forecasting economic growth.  ...  Only during times of financial distress, the indicator increases.  ... 
fatcat:dwxhkjkpzbgxdmtkcyrspceluy

Using text mining of FDA reports to inform early signal detection of cardiovascular lead recalls [article]

Lisa Garnsey Ensign
2021
His enthusiasm for the importance of this work and appreciation of my desire to tackle new horizons will never be forgotten.  ...  To Steve Ross -thank you for introducing me to the world of health information technology, to the subject of natural language processing, and for being someone I could vii confide in when I was deparately  ...  For example, in a dataset with 99% negative and 1% positive samples, one can generate a model with 99% accuracy simply by predicting that all new samples are negative.  ... 
doi:10.25677/myd5-jw86 fatcat:n7bk5awzxncenetu6ba7a37eye

IndieBook

Patricia Minks
2012 unpublished
Then, the reader interacts through a range of possibilities and personalized information is integrated. Finally, the system merges these inputs and defaults and generates narrations.  ...  The socio-historico-spatial setting concretizes the relations and works as a referential frame for the characters and events.  ...  by relations of containment (a room is a subspace of a house)"  ... 
doi:10.25365/thesis.23323 fatcat:mujdei5bvne6ngdibvwlk36zqy

Mapping the Migrant City: Presentations of the Migrant Experience in the Contemporary European Novel 1995-2015

Frances Grahl
2021
fields into a historicised, transnational and postcolonial context.  ...  This thesis is a comparative investigation into contemporary novels of migration to three European capital cities: London, Paris and Rome.  ...  There is no document of civilization which is not at the same time a document of barbarism. 4 Walter Benjamin  ... 
doi:10.25501/soas.00035708 fatcat:66wddxhnhnc2bjktoteu73kagq
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