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VRBagged-Net: Ensemble Based Deep Learning Model for Disaster Event Classification

Muhammad Hanif, Muhammad Atif Tahir, Muhammad Rafi
2021 Electronics  
Users on these social networking sites share both textual and rich content images and videos.  ...  All the datasets belong to the MediaEval Benchmark Workshop, this includes Disaster Image Retrieval from Social Media (DIRSM), Flood Classification for Social Multimedia (FCSM) and Image based News Topic  ...  The ensemble-based deep learning models have provided various useful outcomes in prediction tasks in different research fields including cancer prediction, speech recognition and crude oil price prediction  ... 
doi:10.3390/electronics10121411 fatcat:bqma5u5bj5cbxicyltepf7k4km


Aleksandr Farseev, Ivan Samborskii, Tat-Seng Chua
2016 Proceedings of the 2016 ACM on Multimedia Conference - MM '16  
In this technical demonstration, we propose a cloud-based Big Data Platform for Social Multimedia Analytics called bBridge [9] that automatically detects and profiles meaningful user communities in a specified  ...  The system executes a community detection approach that considers the ability of social networks to complement each other during the process of latent representation learning, while the community profiling  ...  analytics, can be used for Personal Content Filtering and Interest-Based Recommendation.  ... 
doi:10.1145/2964284.2973836 dblp:conf/mm/FarseevSC16 fatcat:qp5fusg3tnhgdat4llmiu5lq3a

Exploring Deep Fusion Ensembling for Automatic Visual Interestingness Prediction [chapter]

Mihai Gabriel Constantin, Liviu-Daniel Stefan, Bogdan Ionescu
2021 Zenodo  
In the context of the ever growing quantity of multimedia content from social, news and educational platforms, generating meaningful recommendations and ratings now requires a more advanced understanding  ...  Further, we explore the possibility of employing a stronger, novel deep learning-based, system fusion for enhancing the performance.  ...  Conclusions This work presents the creation and deployment of a series of deep neural network based ensemble systems, used in the prediction of image and video interestingness.  ... 
doi:10.5281/zenodo.5006827 fatcat:5dsrhoaulzhpjf2jix3v3zw5b4

L-Boost: Identifying Offensive Texts from Social Media Post in Bengali

M. F. Mridha, Md. Anwar Hussen Wadud, Md. Abdul Hamid, Muhammad Mostafa Monowar, M. Abdullah-Al-Wadud, Atif Alamri
2021 IEEE Access  
classifier ensemble for offensive text detection. In Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, [23] Marti A.  ...  The main contributions of this study are learning model based on bidirectional deep learning that summarized as follows: is used for a variety of purposes for  ... 
doi:10.1109/access.2021.3134154 fatcat:jaaavefprne2xlukdtywtxzd6a

Affective Computing for Large-scale Heterogeneous Multimedia Data

Sicheng Zhao, Shangfei Wang, Mohammad Soleymani, Dhiraj Joshi, Qiang Ji
2019 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
The wide popularity of digital photography and social networks has generated a rapidly growing volume of multimedia data (i.e., image, music, and video), resulting in a great demand for managing, retrieving  ...  In this article, we survey the state-of-the-art AC technologies comprehensively for large-scale heterogeneous multimedia data.  ...  In [2] , the results demonstrated that ensemble learning outperforms SVM in terms of classification accuracy.  ... 
doi:10.1145/3363560 fatcat:m56udtjlxrauvmj6d5z2r2zdeu

Multiview Sentiment Analysis with Image-Text-Concept Features of Indonesian Social Media Posts

Esther Setiawan, Institut Sains dan Teknologi Terpadu Surabaya
2021 International Journal of Intelligent Engineering and Systems  
Then we combined predicted probabilities from each classifier for Image, Text, and Concept by Ensemble Learning.  ...  Additionally, we analyzed concepts from texts with SenticNet 5 as a knowledge base model and extracted concepts from images using the DeepSentiBank model.  ...  Conflicts of Interest The authors declare no conflict of interest. Author Contributions Conceptualization, Esther I. Setiawan  ... 
doi:10.22266/ijies2021.0430.47 fatcat:5ijlzaoyezdhrbm2zxosotdfka

Natural Disasters Detection in Social Media and Satellite imagery: a survey [article]

Naina Said, Kashif Ahmad, Michael Regular, Konstantin Pogorelov, Laiq Hassan, Nasir Ahmad, Nicola Conci
2019 arXiv   pre-print
The analysis of natural disaster-related multimedia content got great attention in recent years.  ...  of disaster-related visual content from social media; and (iii) disaster detection in satellite imagery.  ...  The geo-location information associated with multimedia content is then used to map the multimedia content on the satellite imagery.  ... 
arXiv:1901.04277v1 fatcat:5zidbp3owbe6ld33pt4j3aijtq

Classic-Simulation Android Based Game of Fly and Learn in Elementary School Level

Diana Diana, Dion Darmawan
2015 ComTech  
The results achieved in the form of an application that can make a learning media for elementary school level students through the medium of game based on android.  ...  The purpose of this research is to design classic simulation game application of Fly and Learn which is a mobile gaming application based on android smartphone that aims to provide children in elementary  ...  Education and psychology studies have used motivational construction called achievement goals to predict learning success and response to failure (Heeter, Lee, Medler and Magerko, 2011) .  ... 
doi:10.21512/comtech.v6i3.2258 fatcat:442dt2up4rbthniihxct3g3wze

Personalised Network Activity Feeds: Finding Needles in the Haystacks [chapter]

Shlomo Berkovsky, Jill Freyne
2014 Lecture Notes in Computer Science  
The volume of user generated content for discovery on social networks is overwhelming and ever growing, and while time spend on social networking sites has increased, the flood of incoming information  ...  In this chapter, we survey and examine the various research approaches for the personalisation of social network news feeds and identify the synergies and challenges faced by research in this space.  ...  To learn more, Deuker and Albers investigated user priorities for news feed content in a series of structured interviews aimed at uncovering the factors that determine content attractiveness in social  ... 
doi:10.1007/978-3-319-14723-9_2 fatcat:jgfdcxe7nrbetjfagxlmjr3efy

Estimation of Success in Collaborative Learning Based on Multimodal Learning Analytics Features

Daniel Spikol, Emanuele Ruffaldi, Lorenzo Landolfi, Mutlu Cukurova
2017 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)  
Multimodal learning analytics offer researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments.  ...  This paper investigates high-fidelity synchronised multimodal recordings of small groups of learners interacting from diverse sensors that include computer vision, user generated content, and data from  ...  Then, using these classifiers, we identified the most effective features of MMLA to predict the students' group performances in practice-based learning activities.  ... 
doi:10.1109/icalt.2017.122 dblp:conf/icalt/SpikolRLC17 fatcat:ep5g6kpvwzbmdigs2r3xxrtewm

Computational personality recognition in social media

Golnoosh Farnadi, Geetha Sitaraman, Shanu Sushmita, Fabio Celli, Michal Kosinski, David Stillwell, Sergio Davalos, Marie-Francine Moens, Martine De Cock
2016 User modeling and user-adapted interaction  
Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data.  ...  A variety of approaches have been recently proposed to automatically infer users' personality from their user generated content in social media.  ...  This work was funded in part by the SBO-program of the Flemish Agency for Innovation by Science and Technology (IWT-SBO-Nr. 110067).  ... 
doi:10.1007/s11257-016-9171-0 fatcat:33aojvt255hnljkvsiaoonikiq

Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities

Zeshan Fayyaz, Mahsa Ebrahimian, Dina Nawara, Ahmed Ibrahim, Rasha Kashef
2020 Applied Sciences  
Recommender systems are widely used to provide users with recommendations based on their preferences.  ...  With the ever-growing volume of information online, recommender systems have been a useful tool to overcome information overload.  ...  Another multimedia RS model is presented in [85] , which uses social relationship mining methods and movies' metadata, users' comments, and conversation content.  ... 
doi:10.3390/app10217748 fatcat:vihdurtwrzcsxktolbgd6lqg7y

Predicting Age Groups of Reddit Users based on Posting Behavior and Metadata: Comparative Study of Classification Models (Preprint)

Rob Chew, Caroline Kery, Laura Baum, Thomas Bukowski, Annice Kim, Mario Navarro
2020 JMIR Public Health and Surveillance  
We aimed to develop a machine learning algorithm that predicts the age segment of Reddit users, as either adolescents or adults, based on publicly available data.  ...  We ran multiple classification algorithms and tested the performance of the models (precision, recall, F1 score) in predicting the age segments of the users in the labeled data.  ...  This work was funded by contract with Center for Tobacco Products, US Food and Drug Administration, US Department of Health and Human Services (No. HHSF223201510002B-Order #75F40119F19020).  ... 
doi:10.2196/25807 pmid:33724195 fatcat:dfrw3oywzjchllwjlivttwvrm4

Big Educational Data & Analytics: Survey, Architecture and Challenges

Li-Minn Ang, Feng Lu Ge, Kah Phooi Seng
2020 IEEE Access  
focus, social media data in education, etc.  ...  The final part of the paper discusses social (e.g. privacy and ethical issues) and technological challenges for Big data in education.  ...  The sets of users which have the strongest correlation in the past will be identified as nearest neighbors, and the score of the new items will be predicted based upon the scores of its nearest neighbors  ... 
doi:10.1109/access.2020.2994561 fatcat:hmso2cqoofajfgu67hhjzs4jyy

An Ensemble Classifier with Case-Based Reasoning System for Identifying Internet Addiction

Wen-Huai Hsieh, Dong-Her Shih, Po-Yuan Shih, Shih-Bin Lin
2019 International Journal of Environmental Research and Public Health  
In order to detect users with Internet addiction and disabuse their inappropriate behavior early, a secure Web service-based EMBAR (ensemble classifier with case-based reasoning) system is proposed in  ...  The EMBAR system monitors users in the background and can be used for Internet usage monitoring in the future.  ...  Acknowledgments: The authors would like to thank Kimberly Young offering the IAT for use in this academic research. All license fees have been paid before using IAT in this study.  ... 
doi:10.3390/ijerph16071233 pmid:30959905 pmcid:PMC6479715 fatcat:swgqvbmzlfgtpayopvqczxxsza
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