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SPHINX Decision Support Engine v1

Panagiotis Panagiotidis
2020 Zenodo  
The goal is to promote decision-making based both on human and technological agents' intelligence.  ...  This document, which is the first version of a set of two deliverables, entails information on both the SPHINX Decision Support System (DSS) and Analytic Engine (AE), in order to provide an overview of  ...  before the attack occurrence Algorithms Overall Accuracy Micro F-score Macro F-score XGBoost 99% 99% 94% Random Forest 92% 92% 70% Decision Tree 91% 91% 70% Table 7 7 The results  ... 
doi:10.5281/zenodo.4280567 fatcat:i3utedok7zaxtlxzxykoot6b44

Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination

Vibhuti Gupta, Kwanghee Jung, Seung-Chul Yoo
2020 Multimodal Technologies and Interaction  
content evolution, a lack of explicit visual elements, and people's informal behavior in liking, commenting on, and viewing the images.  ...  Our approach provides a proof of concept for an artificial intelligence (AI)-based real-time content management system, which will help to promote a tourist destination.  ...  Random Forest Regression Model Random forest [42] is an ensemble learning model that fits multiple regression trees on random samples of the input data and makes predictions by combining the predictions  ... 
doi:10.3390/mti4030064 fatcat:6wbmdnhhczbshk4l7vugyq25li

Special Issue on Applied Machine Learning

Grzegorz Dudek
2022 Applied Sciences  
Machine learning (ML) is one of the most exciting fields of computing today [...]  ...  Micro-blogs, such as Twitter, have become important tools to share opinions and information among users.  ...  In [23] , for weekly prediction of heatrelated damages, a random forest model was developed using statistical, meteorological, and floating population data.  ... 
doi:10.3390/app12042039 fatcat:ulzgar3shfbmrprd2fpskws7oa

Cricket Match Analytics Using the Big Data Approach

Mazhar Javed Awan, Syed Arbaz Haider Gilani, Hamza Ramzan, Haitham Nobanee, Awais Yasin, Azlan Mohd Zain, Rabia Javed
2021 Electronics  
Cricket is one of the most liked, played, encouraged, and exciting sports in today's time that requires a proper advancement with machine learning and artificial intelligence (AI) to attain more accuracy  ...  The experimental results are measured through accuracy, the root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE), respectively 95%, 30.2, 1350.34, and 28.2 after applying  ...  Similarly, the Random Forest model was applied, which predicted 71% accuracy, but in the XGBoost learning model, an accuracy of 94.23% was seen.  ... 
doi:10.3390/electronics10192350 fatcat:x6pkcqvzzrdaxntmo5b54g26fy

Sentiment Analysis on Social Media for Albanian Language

Roland Vasili, Endri Xhina, Ilia Ninka, Dhori Terpo
2021 OALib  
The purpose of this paper is to test and review different approaches in Sentiment Analysis for messages in the Albanian language found on Twitter.  ...  Additionally, we compare the results among different methods and note the challenges that arise while finally we suggest future directions for further research.  ...  Many messages appear daily in micro-blogging media such as Facebook 4 we can save and potentially study.  ... 
doi:10.4236/oalib.1107514 fatcat:hkbt7ftxvnhtxapkelt75ulkdy

Deep Learning for Financial Applications : A Survey [article]

Ahmet Murat Ozbayoglu, Mehmet Ugur Gudelek, Omer Berat Sezer
2020 arXiv   pre-print
We not only categorized the works according to their intended subfield in finance but also analyzed them based on their DL models.  ...  Finance is one particular area where DL models started getting traction, however, the playfield is wide open, a lot of research opportunities still exist.  ...  Niimi [83] used UCI credit approval dataset 1 to compare DL, SVM, Logistic Regression (LR), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and provided information about credit fraud and credit  ... 
arXiv:2002.05786v1 fatcat:p4ykvxempzajpo66p2z6xaddp4

Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021 [article]

Karl-Herbert Schäfer
2021 arXiv   pre-print
The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.  ...  The TriRhenaTech alliance presents the accepted papers of the 'Upper-Rhine Artificial Intelligence Symposium' held on October 27th 2021 in Kaiserslautern, Germany.  ...  (Charité, Institute of Pathology) for helpful comments and acknowledge the financial support by the Federal Ministry of Education and Research of Germany (BMBF) in the project deep.HEALTH (13FH770IX6).  ... 
arXiv:2112.05657v1 fatcat:wdjgymicyrfybg5zth2dc2i3ni

A MapReduce Opinion Mining for COVID-19-Related Tweets Classification Using Enhanced ID3 Decision Tree Classifier

Fatima Es-Sabery, Khadija Es-Sabery, Junaid Qadir, Beatriz Sainz-De-Abajo, Abdellatif Hair, Begona Garcia-Zapirain, Isabel De La Torre-Diez
2021 IEEE Access  
With the ever-spreading of online purchasing websites, micro-blogging sites, and social media platforms, OM in online social media platforms has picked the interest of thousands of scientific researchers  ...  The obtained textual data (reviews, tweets, or blogs) are classified into three different class labels which are negative, neutral and positive for analyzing and extracting relevant information from the  ...  (iv) Value: the rich data hidden in the generated tweets are a hot research area for scientific researchers in the Big Data and sentiment analysis field, and also a robust tool for organizations and governments  ... 
doi:10.1109/access.2021.3073215 fatcat:rk4qmvs4cjctblwnkrrq2bd32i

A MapReduce Opinion Mining for COVID-19-Related Tweets Classification Using Enhanced ID3 Decision Tree Classifier

Junaid Qadir
2021 figshare.com  
With the ever-spreading of online purchasing websites, micro-bloggingsites, and social media platforms, OM in online social media platforms has picked the interest of thousandsof scientific researchers  ...  The obtained textual data (reviews,tweets, or blogs) are classified into three different class labels which are negative, neutral and positive foranalyzing and extracting relevant information from the  ...  (iv) Value: the rich data hidden in the generated tweets are a hot research area for scientific researchers in the Big Data and sentiment analysis field, and also a robust tool for organizations and governments  ... 
doi:10.6084/m9.figshare.14460009.v1 fatcat:m7mitgapprhnnp3km67afbxh7a

Organic Computing

(:Unkn) Unknown, Universität Kassel, Sven Tomforde, Christian Krupitzer
2021
Acknowledgements The project Incident-aware Resilient Traffic Management for Urban Road Networks (InTURN) is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), TO-843/5-1.  ...  Acknowledgements The authors would like to thank the German research foundation (Deutsche Forschungsgemeinschaft, DFG) for the financial support in the context of the "Organic Computing Techniques for  ...  Then, a random forest classification model is learned for each forecasting method, which estimates whether the respective forecasting method could perform best considering the time series characteristics  ... 
doi:10.17170/kobra-202103173535 fatcat:wzlt3ciljzejfdg5ahfc7iwreq

Mapping (Dis-)Information Flow about the MH17 Plane Crash

Mareike Hartmann, Yevgeniy Golovchenko, Isabelle Augenstein
2019 Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda   unpublished
We are also thrilled to be able to bring an invited speaker, Elissa Redmiles from Princeton University and Microsoft Research, with a talk on measuring human perception to defend democracy, exploring a  ...  Fourteen participants submitted a system description paper, which include models based on a wide range of learning models (e.g., neural networks, logistic regression) and representations (e.g., manually-engineered  ...  The project is developed in collaboration between the Qatar Computing Research Institute (QCRI), HBKU and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).  ... 
doi:10.18653/v1/d19-5006 fatcat:77l3dndrkvfmlhjt6qvnrassgi