Computer Engineering Commons^™

Bibliometric Analysis Of Emerging Technologies In The Field Of Computer Science Helping In Ovarian Cancer Research, Sonali Kothari Dr., Anvita Gupta, Muskaan Agrawal Agrawal, Kajal Jaggi, Adhiraj Dev Goswami, Ketan Kotecha, M. Karthikeyan Dr., Vijayshri Khedkar

Library Philosophy and Practice (e-journal)

This study is carried out to provide an analysis of the literature available at the intersection of ovarian cancer and computing. A comprehensive search was conducted using Scopus database for English-language peer-reviewed articles. The study administers chronological, domain clustering and text analysis of the articles under consideration to provide high-level concept map composed of specific words and the connections between them.

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is …

Indonesian Library User Behaviour During Covid 19 Pandemic On Digital Library Platform, Irhamni

English Language Institute

COVID-19 pandemic has significantly changed library user behavior, workplaces, and some public areas including in the library. During the COVID 19 pandemics, the digital library with a mobile app like ipusnas has facilitated to accessing library resources. The ipusnas has increased people's accessibility to library materials. This research focuses on the use of the digital library has a significant impact on library users behavior; it can influence how they read, access the library, and their interaction with the library resources.

Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique, Seong-Yong Hong, Juyun Cho, Yonghyun Hwang

Journal of International Technology and Information Management

With the recent advances in computer technology along with pervasive internet accesses, data analytics is getting more attention than ever before. In addition, research areas on data analysis are diverging and integrating lots of different fields such as a business and social sector. Especially, recent researches focus on the data analysis for a better intelligent decision making and prediction system. This paper analyzes data collected from current IT learners who have already studied various IT subjects to find the IT learners’ learning patterns. The most popular learning patterns are identified through an association rule data mining using an arules package …

Evaluation Of Classification And Ensemble Algorithms For Bank Customer Marketing Response Prediction, Olatunji Apampa

Journal of International Technology and Information Management

This article attempts to improve the performance of classification algorithms used in the bank customer marketing response prediction of an unnamed Portuguese bank using the Random Forest ensemble. A thorough exploratory data analysis (EDA) was conducted on the data in order to ascertain the presence of anomalies such as outliers and extreme values. The EDA revealed that the bank data had 45, 211 instances and 17 features, with 11.7% positive responses. This was in addition to the detection of outliers and extreme values. Classification algorithms used for modelling the bank dataset include; Logistic Regression, Decision Tree, Naïve Bayes and the …

Data Mining The Harness Track And Predicting Outcomes, Robert P. Schumaker

Journal of International Technology and Information Management

This paper presented the S&C Racing system that uses Support Vector Regression (SVR) to predict harness race finishes and analyzed it on fifteen months of data from Northfield Park. We found that our system outperforms the most common betting strategies of wagering on the favorites and the mathematical arbitrage Dr. Z system in five of the seven wager types tested. This work would suggest that an informational inequality exists within the harness racing market that is not apparent to domain experts.