Journal ArticleDOI
A Neuro-Fuzzy Approach to Detect Rumors in Online Social Networks
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TLDR
Experimental results show proposed approaches to tackling Rumor Classification and Rumor Detection problems are well-suited to solve common problems.Abstract:
Alongwithtrueinformation,rumorsspreadinonlinesocialnetworks(OSN)onanunprecedented scale.Inrecentdays,rumoridentificationgainsmoreinterestamongtheresearchers.Findingrumors alsoposesothercriticalchallengeslikenoisyandimpreciseinputdata,datasparsity,andunclear interpretationsoftheoutput.Toaddresstheseissues,weproposeaneuro-fuzzyclassificationapproach calledtheneuro-fuzzyrumordetector(NFRD)toautomaticallyidentifytherumorsinOSNs.NFRD quicklytransformstheinputtofuzzyruleswhichclassifytherumor.Neuralnetworkshandlelarger inputdata.Fuzzysystemsarebetterinhandlinguncertaintyandimprecisionininputdatabyproducing fuzzyrulesthateffectivelyeliminatetheunclearinputs.NFRDalsoconsidersthesemanticaspects ofinformationtoensurebetterclassification.Theneuro-fuzzyapproachaddressesthemostcommon problemssuchasuncertaintyelimination,noisereduction,andquickergeneralization.Experimental resultsshowtheproposedapproachperformswellagainststate-of-the-artrumordetectingtechniques. KeyWORDS Cyber Security, Deep Learning, Fuzzy System, Neural Networks, Neuro-Fuzzy System, Online Social Network, Rumor Classification, Rumor Detectionread more
Citations
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Journal ArticleDOI
Integrating machine learning and open data into social Chatbot for filtering information rumor.
I-Ching Hsu,Chun-Cheng Chang +1 more
TL;DR: A general architecture that integrates machine learning and open data with a Chatbot and is based cloud computing (MLODCCC), which can assist users in evaluating information authenticity on social platforms is proposed.
Journal ArticleDOI
The SEIRS-C model of information diffusion based on rumour spreading with fuzzy logic in social networks
Book ChapterDOI
Modeling, Analysis, of Induction Motor's Stator Turns Fault Using Neuro-Fuzzy
TL;DR: This chapter discusses modeling and analysis methods for fault detection and diagnosis of stator inter-turn short circuit in three-phase induction machines in Matlab/Simulink® software.
Proceedings ArticleDOI
Rumor Remove Order Strategy on Social Networks
TL;DR: Wang et al. as mentioned in this paper proposed two rumor control strategies to remove the multiple rumors in a certain order, i.e., the order of removing rumors matters as different rumors possess different properties, e.g., acceptance rate, propagation speed, etc.
References
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Proceedings Article
Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot,Yoshua Bengio +1 more
TL;DR: The objective here is to understand better why standard gradient descent from random initialization is doing so poorly with deep neural networks, to better understand these recent relative successes and help design better algorithms in the future.
Proceedings Article
Distributed Representations of Sentences and Documents
Quoc V. Le,Tomas Mikolov +1 more
TL;DR: Paragraph Vector is an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts, such as sentences, paragraphs, and documents, and its construction gives the algorithm the potential to overcome the weaknesses of bag-of-words models.
Book
Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence
TL;DR: This text provides a comprehensive treatment of the methodologies underlying neuro-fuzzy and soft computing with equal emphasis on theoretical aspects of covered methodologies, empirical observations, and verifications of various applications in practice.
Journal ArticleDOI
Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]
TL;DR: Interestingly, neuro fuzzy and soft computing a computational approach to learning and machine intelligence that you really wait for now is coming.
Posted Content
Distributed Representations of Sentences and Documents
Quoc V. Le,Tomas Mikolov +1 more
TL;DR: The authors proposed paragraph vector, an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts, such as sentences, paragraphs, and documents, and achieved new state-of-the-art results on several text classification and sentiment analysis tasks.
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