Entity analysis in natural language processing involves solving multiple structured prediction problems such as mention detection, coreference resolution, and entity linking. We explore the space of search-based learn...
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As the prominence of networking through social media is intensifying, the people's interest is also tuned towards extensive usage of social media for showcasing their current activities. An important kind of onlin...
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As the prominence of networking through social media is intensifying, the people's interest is also tuned towards extensive usage of social media for showcasing their current activities. An important kind of online data threat is cyberbullying which is described as the intentional and repeated use of technology by a person or group of individuals to upset or harm a person's or community's social-psychological attitude. Generally, cyberbullying and prejudice based on gender, ethnicity, physical and mental disabilities and religion are frequently linked from the text, image, audio and videos disclosed by the user. Cyberbullying might lead to many negative consequences like high risks of losing self-confidence, depression, disclosure of sensitive private information leading to self-harm and suicide. These impacts necessitate the need for analyzing the harmful bullying and discriminative social media posts and support the users by protecting them from regrets and depression. This research work is a comparison of the stateof-art models that can be used for identifying the cyberbullying content posted on a social media platform and classifies the severity of the content. The user generated content (UGC) is highly varied from Twitter. Two Machine learning models namely SVM (Accuracy - 84%) and Naïve Bayes (Accuracy - 83%) were tested. The accuracies were found to be low due to the instability and the complexity of the model, and the highly dynamic nature of variables. Hence, Deep learning models were tested as they use Natural Language Processing and Predictive Modeling which gives high accuracies. Six Deep learning models namely BiLSTM + Fasttext (Accuracy - 84.83%), BiLSTM + GloveTwitter (Accuracy - 85.83%), BERTBase (Accuracy - 89%), RoBERTa (Accuracy - 89.14%), DistilBERT (Accuracy - 87.09%), BERTweet (Accuracy - 93%) were tested and BERTweet was found to have the highest accuracy since BERTweet model has been trained with data specific to Twitter. This research work i
This study aimed to propose a detection approach for plant disease based on deep learning (DL) algorithms. The study sought to discover diseases affecting three plants, which are: Common Rust, Vercospora Leaf Spot, No...
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Analysing coronary artery plaque segments with respect to their functional significance and therefore their influence to patient management in a non-invasive setup is an important subject of current research. In this ...
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Social media has become more prevalent and it is now fairly easy to communicate with people online. Social network users have many options to cooperate, interact positively, and exchange information. The same system m...
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Use of digital technologies lead to the development of cyberbullying and social media has become a major source for it compared to mobile phones, platforms such as gaming and messaging. Cyberbullying can take several ...
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In this paper we explore several issues relevant to the benchmarking and comparison of machine learning algorithms. We illustrate those issues with a case study using the decision tree induction algorithms C4.5 and Mu...
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In this paper we explore several issues relevant to the benchmarking and comparison of machine learning algorithms. We illustrate those issues with a case study using the decision tree induction algorithms C4.5 and Multiscale Classification (MSC), Multi-layer perceptrons (MLP) and Multi-variable regression (MVR). Then for a `real world' problem we compare estimates of the true error rates for each classifer, first on a single train-and-test partition, and then using cross validated sub-sampling techniques. The relevance of the χ2 test is then discussed in relation to comparing the classifer accuracies. The paper concludes by evaluating the performance of these four fundamentally different approaches to the solution of this regression problem.
Popularity of social media has increased rapidly and now it is very easy to interact with different persons across social media. As a result, cyberbullying towards people across social media has also increased. As cyb...
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Fake news is appearing in the news a number of Business, Communities, Political and others reasons and being common in the air world. Humans can be infected it is easy with these false stories of the words which the p...
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Maintenance of the patient respiratory passage (airway) open and unobstructed breathing is a foremost duty of an anesthesiologist or other physicians who are involved in patient care under emergency situations. One of...
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