An Efficient Mining for Recommendation System for Academics

Akhtar, Naseem; Agarwal, Pragya

doi:10.35940/ijrte.e5924.018520

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…There are a lot of services out there that rely on machine learning algorithms. Computing models known as machine learning algorithms enable computers to recognize patterns in data, make predictions [31] or assessments based on that data [32], and all without human intervention or explicit programming. Image and audio recognition, recommendation systems, fraud detection, autonomous cars, natural language processing, etc.…”

Section: Machine Learning Algorithmsmentioning

confidence: 99%

Machine Learning for the Diagnosis and Prognosis of Chronic Illnesses

Kajal,

Kanchan Saini,

Dr. Nikhat Akhtar

et al. 2024

Int J Sci Res Sci Eng Technol

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An essential part of healthcare is disease prediction, which seeks to identify people who are at risk of getting certain diseases. Because of their superior capacity to sift through massive datasets in search of intricate patterns, machine learning algorithms have recently become useful instruments in the fight against illness prediction. The goal of this project is to make it easier for people to diagnose their own health problems using just their symptoms and precise vital signs. Due to excessive medical expenditures, many people put off taking care of their health, which can result in worsening symptoms or even death. Medical expenses can be overwhelming for people without health insurance. Using machine learning methods like ExtRa Trees, the suggested system provides a general illness forecast based on patients' symptoms. The algorithm provides a possible diagnosis based on the user's age, gender, and symptoms, suggesting that the user may be experiencing a certain illness. The system also suggests healthy eating and exercise routines to help lessen the impact of the condition, depending on how bad it is. Lastly, this article has shown a comparison examination of the suggested system using several algorithms including logistic regression, decision tree, and Naïve Bayes. The efficiency and accuracy of illness prediction are both enhanced by the suggested model.

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Section: Machine Learning Algorithmsmentioning

confidence: 99%

Machine Learning for the Diagnosis and Prognosis of Chronic Illnesses

Kajal,

Kanchan Saini,

Dr. Nikhat Akhtar

et al. 2024

Int J Sci Res Sci Eng Technol

View full text Add to dashboard Cite

show abstract

“…The naive Bayes classifier is a probabilistic classifier built on the Bayes theorem that operates on the presumption that each feature contributes equally and independently to the target class [49]. The NB classifier makes the assumption that each feature is separate from the others and does not interact, therefore each feature independently and equally influences the likelihood that a sample belongs to a given class.…”

Section: Naive Bayes (Nb)mentioning

confidence: 99%

“…Based on a variety of account criteria, neural networks [11] and SVM are appropriate for detecting phony accounts on social networking sites since they can take a significant quantity of random input [12]. On the Bayes theorem, the Naive Bayes classifier [13] is based. It forecasts the likelihood that a particular variable belongs to a specific class.…”

mentioning

confidence: 99%

Novel Approaches to Detect Phony Profile on Online Social Networks (OSNs) Using Machine Learning

et al. 2023

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Currently, almost everyone spends more time on online social media platforms engaging with and exchanging information with people from all over the world, from children to adults. Our lives are greatly influenced by social media sites like Twitter, Facebook, Instagram, and LinkedIn. The social network is evolving into a well-liked platform for connecting with individuals across the globe. Social media platforms exist as a result of the enormous connectivity and information sharing that the internet has made possible. Social media's rising popularity has had both beneficial and detrimental consequences on society. However, it also has to deal with the issue of bogus profiles. False profiles are often constructed by humans, bots, or cyborgs and are used for phishing, propagating rumors, data breaches, and identity theft. Thus, we are emphasizing in this post the significance of setting up a system that can identify false profiles on social media networks. To illustrate the suggested concept of machine learning-based false news identification, we used the Twitter dataset for phony profile detection. The suggested model involves pre-processing to improve the dataset's quality and minimize its dimensions by modifying its contents and features. To forecast the bogus profiles, the widely used machine learning algorithms are used.

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A Systematic Literature Review on the Cyber Security

Perwej

Abbas

Dixit³

et al. 2021

int.jour.sci.res.mana.

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In recent years, the Internet has become an integral element of people's everyday lifestyles all across the world. Online criminality, on the other hand, has risen in tandem with the growth of Internet activity. Cyber security has advanced greatly in recent years in order to keep up with the rapid changes that occur in cyberspace. Cyber security refers to the methods that a country or organization can use to safeguard its products and information in cyberspace. Two decades ago, the term "cyber security" was barely recognized by the general public. Cyber security isn't just a problem that affects individuals but it also applies to an organization or a government. Everything has recently been digitized, with cybernetics employing a variety of technologies such as cloud computing, smart phones, and Internet of Things techniques, among others. Cyber-attacks are raising concerns about privacy, security, and financial compensation. Cyber security is a set of technologies, processes, and practices aimed at preventing attacks, damage, and illegal access to networks, computers, programmes, and data. The primary goal of this article is to conduct a thorough examination of cyber security kinds, why cyber security is important, cyber security framework, cyber security tools, and cyber security difficulties. Cyber security safeguards the data and integrity of computing assets that are part of or connected to an organization's network, with the goal of defending such assets from all threat actors throughout the life cycle of a cyber-attack.

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An Efficient Mining for Recommendation System for Academics

Cited by 9 publications

References 15 publications

Machine Learning for the Diagnosis and Prognosis of Chronic Illnesses

Machine Learning for the Diagnosis and Prognosis of Chronic Illnesses

Novel Approaches to Detect Phony Profile on Online Social Networks (OSNs) Using Machine Learning

A Systematic Literature Review on the Cyber Security

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