Implementation of Novel Machine Learning Methods for Analysis and Detection of Fake Reviews in Social Media

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), Journal Year: 2023, Volume and Issue: unknown, P. 243 - 250

Published: March 23, 2023

Now-a-days social media plays a key role in our daily life. For many things we rely on this media. This very crucial several fields. People started believing the which are written internet before taking their decisions, such as having look reviews for various purposes like buying product online or booking hotel room vacation visiting place, all these people by people. By there will be advantages well disadvantages. Some to improve company standards high lightening products, they generate few fake attracts users towards them and that starts choosing them. A target object's positive ratings may draw more consumers boost sales, whereas negative result less demand lower sales. Our research aims determine if review is genuine fraudulent. To avoid go with need detection system. In system some machine learning techniques used. The proposed method consists of algorithms. They performed benchmark analysis different types (1) traditional ML algorithms logistic regression (LR), support vector machines (SVM), decision trees (DT), Naive bayes (NB), random forests (RF), & XG Boost (XGB), an ensemble approach algorithms, (2) cutting-edge bidirectional long short-term memory (BIIS TM), etc. These assist identifying bogus reviews. contrasted one another provide precise results.

Language: Английский

---

APPLYING THE MODULAR ENCRYPTION STANDARD TO MOBILE CLOUD COMPUTING TO IMPROVE THE SAFETY OF HEALTH DATA

Journal of Pharmaceutical Negative Results, Journal Year: 2022, Volume and Issue: unknown, P. 1911 - 1917

Published: Nov. 10, 2022

Mobile Cloud Computing (MCC) has numerous and easily observable benefits in healthcare, but its growth is being hampered by protection security concerns. The problem at hand calls for one's whole attention seriousness if one to grasp scope make good use of it. A global, territorial, local effort required disseminate health information. To completely profit the wellbeing administrations, it significant set up requested rehearses counteraction safety breaks weaknesses.

Language: Английский

---

CNN BASED PATHWAY CONTROL TO PREVENT COVID SPREAD USING FACE MASK AND BODY TEMPERATURE DETECTION

Journal of Pharmaceutical Negative Results, Journal Year: 2022, Volume and Issue: 13(SO4)

Published: Jan. 1, 2022

Airborne diseases cause detriment in the human life.Many were found history such as TB, SARS, MERS and recently COVID 19.These hit dead rate crushes health wealth of world population.Mostly, airborne will spread rapidly crowdy places.Especially, case COVID-19, Wearing mask monitoring body temperature by individual is good solution to prevent rapid disease.So, keeping safety measures face crucial places Airports, railway stations, Bus Stations, malls, temples, etc. obligatory.With a focus on emphasizing people we proposed integrated system that monitors each open/close pathway gate allow after knee verification.Proposed Prototype uses Raspberry pi monitor Face using CNN Arduino enable motor drivers open or close Gate.Efficiency loss Proposed model was trained tested with multiple epoches.

Language: Английский

---

An effectual recommendation model using hybrid learning models for early detection of Alzheimer’s disease

Intelligent Decision Technologies, Journal Year: 2024, Volume and Issue: 18(2), P. 1541 - 1556

Published: Feb. 9, 2024

Alzheimer’s disease (AD) is a neurodegenerative disorder that affects millions of individuals worldwide, causing progressive cognitive decline. Early prediction and diagnosis the AD accurately crucial for effective intervention treatment. In this study, we propose comprehensive framework using various techniques, including preprocessing denoising with Multilayer Perceptron (MLP) Ant Colony Optimization (ACO), segmentation U-Net, classification Spatial Pyramid Pooling Network (SPPNet). Furthermore, employ Convolutional Neural (CNN) SPPNet training develop chatbot recommendation based on MRI data input. The techniques play vital role in enhancing quality input data. MLP utilized preprocessing, where it effectively handles feature extraction noise reduction. ACO employed denoising, optimizing to improve signal-to-noise ratio, overall performance subsequent stages. For accurate brain regions, U-Net architecture, which has shown remarkable success medical image tasks. identifies regions interest, aiding phase utilizes SPPNet, deep learning model known its ability capture spatial information at multiple scales. extracts features from segmented enabling robust non-AD cases. To enhance process, CNN leveraging power convolutional layers intricate patterns predictive accuracy. CNN-SPPNet trained large dataset scans, learn complex representations make predictions. Hence proposed work can be integrated takes as provides recommendations predicted probability. Experimental evaluation shows combination segmentation, offers solution efficient management.

Language: Английский

---

Multi-filter-Based Image Pre-processing on Face Mask Detection Using Custom CNN Architecture

Smart innovation, systems and technologies, Journal Year: 2024, Volume and Issue: unknown, P. 29 - 36

Published: Oct. 17, 2024

Language: Английский

---

Big Data Analytics Survey: Environment, Technologies, and Use Cases

Published: Sept. 18, 2024

Language: Английский

---

Dimensions of Automated ETL Management: A Contemporary Literature Review

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS), Journal Year: 2022, Volume and Issue: unknown, P. 1292 - 1297

Published: Dec. 13, 2022

ETL solutions are becoming more widely used because of the increasing complexity data systems and importance high-quality sources processing for making decisions. The raw is retrieved placed into a designated warehouse efficient information analysis processing. Using management technologies to acquire insights functional operational elements one critical components software engineering in present environment. There need improve performance real-time applications. However, several scholarly business investigations have been efficacy dynamics technologies. As result, it essential look at methods effectiveness processes meet immediate demands operations. This paper explores existing systems' history, constraints, potential, how machine learning models integrated processes. as evidenced by review relevant academic literature, there widespread support using perfect Although many can be helpful processing, only tiny fraction market products use them all. Machine learning-based optimize ETL-based management, concentrating on limits future potential.

Language: Английский

---

Classification of Mask Use during a Pandemic using the CNN Algorithm with Voice Notifications

Edutran Computer Science and Information Technology, Journal Year: 2023, Volume and Issue: 1(1), P. 26 - 33

Published: March 13, 2023

Various technologies were created to prevent the threat of Covid-19 virus, which has spread in many countries including Indonesia. One them is use masks public places. With this mind, study aims detect facial objects. Based on Kaggle website, object used for research a human face 2D form. This consists two stages, namely creating and testing model. The model system that detects classifies faces with masks, inappropriate without masks. Then tested its accuracy. result thirty trials, an accuracy 99% using webcam real time. sound indicator notification Convolutional Neural Network (CNN) algorithm method.

Language: Английский

---