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Chapter and Conference Paper
Bayesian Optimized Traffic Sign Recognition on Social Media Data Using Deep Learning
One of the distinguishing features of traffic signs is the wide variation in their visual appearance in actual environments. Road signs are affected, for example, by variations in lighting, shifting weather pa...
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Chapter and Conference Paper
Empirical Analysis on Fake News Detection Using Feature Extraction and Feature Optimization Techniques
With the rapid growth of technology and social media, fake news has become a major issue today. Detecting and preventing fake news is becoming increasingly difficult and is a significant problem that requires ...
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Article
Manifestation of customer value co-creation behaviour in the automobile industry: a perspective from Twitter analytics
As firms and customers seek new synergies, value co-creation emerges as an imperative that straddles almost all sectors. This paper corroborates the manifestation of customer value co-creation behaviour in the...
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Chapter and Conference Paper
Empirical Analysis of Depression Detection Using Deep Learning on Twitter
People spend a major portion of their time from their daily routine over social media platforms. Many researchers have previously attempted to examine the mental status of the users through their thoughts and ...
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Chapter and Conference Paper
Cataract Detection on Ocular Fundus Images Using Machine Learning
Cataract is a very common condition affecting the elderly. The onset of cataract is slow and is therefore not detected until it starts to obstruct the vision of the affected patient. One way to detect cataract...
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Article
Multimodal cyberbullying detection using capsule network with dynamic routing and deep convolutional neural network
Cyberbullying is the use of information technology networks by individuals’ to humiliate, tease, embarrass, taunt, defame and disparage a target without any face-to-face contact. Social media is the 'virtual p...
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Article
Multi-input integrative learning using deep neural networks and transfer learning for cyberbullying detection in real-time code-mix data
Automatic detection of cyberbullying in social media content is a natural language understanding and generic text classification task. The cultural diversities, country-specific trending topics hash-tags on so...
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Article
A Bi-GRU with attention and CapsNet hybrid model for cyberbullying detection on social media
As a constructive mode of information sharing, collaboration and communication, social media platforms offer users with limitless opportunities. The same hypermedia can be transposed into a synthetic and toxic...
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Chapter and Conference Paper
Lung Cancer Detection Using Ensemble Learning
From time to time, lung cancer has appeared in the category of nearly the most lethal maladies since humankind existed. It is even among the most incessant fatalities and major reasons of mortality among all c...
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Chapter and Conference Paper
Rumour Stance Classification on Textual Social Media Content Using Machine Learning
Rumour stance classification involves the analysis of how the users react to the rumours linked with the news on social media platforms. It involves the identification of the attitude of the users towards the ...
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Chapter and Conference Paper
Detection of Offensive Comments for Textual Data Using Machine Learning
Social Media is an essential part of our lives today that provides us to connect with others all around the world. Social Media facilitates the sharing and spreading of information, thoughts, and ideas. Howeve...
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Chapter and Conference Paper
Cyberbullying-Mediated Depression Detection in Social Media Using Machine Learning
Mental distress is one of the most paramount causes of disability worldwide. People using social media at an exponential rate becomes prey to cyberbullying victimization, eventually leading to mental health pr...
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Chapter and Conference Paper
Empirical Analysis of Humor Detection Using Deep Learning and Machine Learning on Kaggle Corpus
Humor is a multifaceted personality trait that makes us stand out as individuals and social groups. Humor is an important part of interpersonal communication. Due to its subjective nature, it remains difficult...
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Chapter and Conference Paper
Cyberbullying Checker: Online Bully Content Detection Using Hybrid Supervised Learning
Cyberbullying is primarily associated with the utilization of digital media in order to bully someone. It has grown to a level where it is seriously affecting and damaging individual’s lives where social media...
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Article
Cyberbullying detection on social multimedia using soft computing techniques: a meta-analysis
Cyberbullying is to bully someone in the digital realm. It has become extremely detrimental as the social media and the internet have become more popular and omnipresent. People use the internet services to vi...
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Chapter
Software Release Time Problem Revisited
With technological advancements in the Information Technology (IT) world, Software Reliability Growth Models (SRGMs) have been extensively made use of by both researchers and practitioners. To withstand the ch...
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Chapter
A Hybrid Intuitionistic Fuzzy and Entropy Weight Based Multi-Criteria Decision Model with TOPSIS
In a scenario where decision-makers are always faced with the challenge of selecting the right technology for their IT needs posed due to the availability of multiple advanced technologies in the market and co...
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Chapter and Conference Paper
Analysis of GA Optimized ANN for Proactive Context Aware Recommender System
A Recommender System essentially focusses on recommending the most significant items to the users based on their preferences. The objective of a recommender system is to create relevant suggestions to the user...
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Chapter
Two-Dimensional Framework to Optimize Release Time and Warranty
Today’s customer expectations to have well-developed complex enterprise level software, delivered within no time, have left developers with a dilemma as for how to attain the desired level of software reliabil...
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Chapter
When to Start Remanufacturing Using Adopter Categorization
Remanufacturing of goods involves taking the product back from the customer so as to use it as a feedstock for manufacturing new products. It provides double benefits of cost and environmental saving to the ma...
