Attendance automatic recognition and learning behavior of web-based course attendance based on machine learning algorithms

2020 ◽  
pp. 1-9
Author(s):  
Xianju Fei ◽  
Guozhong Tian
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Automatic Recognition ◽  
Machine Learning Algorithms ◽  
Learning Behavior ◽  
Web Based

scholarly journals Development of a web-based application using machine learning algorithms to facilitate systematic literature reviews

2017 ◽  
Vol 28 ◽  
pp. v518
Author(s):  
H-L. Wong ◽  
T. Luechtefeld ◽  
A. Prawira ◽  
Z. Patterson ◽  
J. Workman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Web Based ◽  
Literature Reviews

scholarly journals An Effective System to Detect Fake Research

2019 ◽  
Vol 9 (1) ◽  
pp. 2971-2975
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Web Based ◽  
User Reviews ◽  
Effective System ◽  
Media Systems ◽  
The Right ◽  
Fake Reviews

Detection of spam review is an important operation for present e-commwebsites and apps.We address the issue on fake review detection in user reviews in e-commerce application, which wasimportant for implementing anti-opinion spam.First we analyze the characteristics of fake reviews and we apply the machine learning algorithms on that data. Spam or fake reviews of the itemsreducing the reliability of decision making and competitive analysis.The presence of fake reviews makes the customer cannot make the right decisions of sellers, which can also causes the goodwill of the platform decreased. There is a chance of leaving appraisals via web-based networking media systems whether states or harming by spammers on specific item, firm alongside their answers by recognizing these spammers just as in like manner spams so as to understand the assessments in the interpersonal organizations sites, we exist a stand-out structure called Netspam which uses spam highlights for demonstrating tribute datasets as heterogeneous subtleties systems to guide spam location treatment directly into gathering issue in such systems.

scholarly journals Analysis and Outcome Prediction of Crowdfunding Campaigns

2022 ◽  
Vol 12 (1) ◽  
pp. 1-14
Author(s):  
Parmeet Kaur ◽  
Sanya Deshmukh ◽  
Pranjal Apoorva ◽  
Simar Batra
Keyword(s):  
Machine Learning ◽  
Outcome Prediction ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
New Venture ◽  
Web Based ◽  
Small Organizations ◽  
Huge Data ◽  
Nosql Database ◽  
Existing Data

Humongous volumes of data are being generated every minute by individual users as well as organizations. This data can be turned into a valuable asset only if it is analyzed, interpreted and used for improving processes or for benefiting users. One such source that is contributing huge data every year is a large number of web-based crowd-funding projects. These projects and related campaigns help ventures to raise money by acquiring small amounts of funding from different small organizations and people. The funds raised for crowdfunded projects and hence, their success depends on multiple elements of the project. The current work predicts the success of a new venture by analysis and visualization of the existing data and determining the parameters on which success of a project depends. The prediction of a project’s outcome is performed by application of machine learning algorithms on crowd-funding data stored in the NoSQL database, MongoDB. The results of this work can prove beneficial for the investors to have an estimate about the success of a project before investing in it.

scholarly journals Machine Learning Algorithms for Spam Detection in Social Networks

2019 ◽  
Vol 8 (S3) ◽  
pp. 41-44
Author(s):  
K. Nagaramani ◽  
K. Vandanarao ◽  
B. Mamatha
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Systems ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Spam Detection ◽  
Web Based ◽  
The Times ◽  
The Web

Most of the web based social systems like Face book, twitter, other mailing systems and social networks are developed for users to share their information, to interact and engage with the community. Most of the times these social networks will give some troubles to the users by spam messages, threaten messages, hackers and so on.. Many of the researchers worked on this and gave several approaches to detect the spam, hackers and other trouble shoots. In this paper we are discussing some tools to detect the spam messages in social networks. Here we are using RF, SVM, KNN and MLP machine learning algorithms across rapid miner and WEKA. It gives the better results when compared with other tools.

scholarly journals Medical Big Data Analytics using Machine Learning Algorithms

2019 ◽  
Vol 9 (1) ◽  
pp. 3517-3526
Keyword(s):  
Machine Learning ◽  
Cost Efficiency ◽  
Learning Algorithms ◽  
Big Data Analytics ◽  
Modern Medicine ◽  
Machine Learning Algorithms ◽  
Web Based ◽  
Medical Big Data ◽  
Systematic Data Collection

Artificial intelligence and expert systems plays a key role in modern medicine sciences for disease prediction, surveillance interventions, cost efficiency and better quality of life etc. With the arrival of new web-based data sources and systematic data collection through surveys and medical reporting, there is a need of the hour to develop effective recommendation systems which can support practitioners in better decision-making process. Machine Learning Algorithms (MLA) is a powerful tool which enables computers to learn from data. While many novel developed MLA constantly evolves, there is need to develop more systematic, robust algorithm which can interpret with highest possible accuracy, sensitivity and specificity. The study reviews previously published series on different algorithms their advantages and limitations which shall help make future recommendations for researchers and experts seeking to develop an effective algorithm for predicting the likelihood of various diseases.

scholarly journals A Survey on Automatic Recognition of Fake Indian Currency Note

2021 ◽  
Vol 9 (VII) ◽  
pp. 2918-2920
Author(s):  
Anisha Parpanathan
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Fraud Detection ◽  
Recognition System ◽  
Automatic Recognition ◽  
Machine Learning Algorithms ◽  
Paper Currency ◽  
Currency Note

The Currency Recognition System was developed for the purpose of fraud detection in paper currency, so this system is u sed worldwide. The uses of this framework can be recognized in banking frameworks, cash observing gadgets, cash trade frameworks. This paper proposes an automatic paper currency recognition system through an application developed using Machine learning Algorithms. The algorithm implemented is simple, robust and efficient.

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