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129 articles for “Data mining Technique”
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A Vital Role of Big Data in Education System: A Review
Abstract: Big data is used in a variety of fields, and we investigate how big data is used in education. The research literature on big data in education from 2010 to 2020 is reviewed, followed by an analysis of big educational data mining techniques, tools, and applications. Using these applications, this study investigates the idea of improving the educational process. Two methods are used to validate the educational process in order …
Published in Journal of Web Engineering & Technology · Vol. 9, Issue 3, 2022 · pp. 13–21 Read article
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Prediction of Compressive Strength of Concrete Using Machine Learning Techniques
Abstract: Compressive strength of concrete is an important parameter for designing any concrete structure. Compressive strength of concrete is a complex nonlinear function of its ingredients. Prediction of Concrete compressive strength plays a vital role in pre design phases of the structure and quality control of construction. The conventional methods of compressive strength determination are time consuming, so the use of data mining methods to predict the strength beforehand is helpful. …
Published in Journal of Construction Engineering, Technology & Management · Vol. 5, Issue 3, 2015 · pp. 34–41 Read article
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An Improved SentiWordNet for Opinion Mining and Sentiment Analysis
Abstract: Opinion Mining and Sentiment Analysis is an emergent research area, spanning over multiple disciplines such as data mining, text mining, etc. Opinion mining is an art of extracting the opinions from the huge set of opinion set or reviews. Sentiment analysis is a type of natural language processing for tracking the mood of the public about a particular product or topic. The existing works of opinion mining used Sentiwordnet as …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 2, 2014 · pp. 1–7 Read article
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A Comparative Study on Detection of Different Disease Using KNN
Abstract: Nowadays many approaches are made to detect or predict any disease in human body using different data mining techniques. This paper is an approach to study K-nearest neighbor (KNN) classification technique used in different disease prediction. Nowadays number of diseases are needed to be classified and are threat to the human life. Here KNN approach on disease are tuberculosis, heart disease, diabetes, chronic renal failure, neuromuscular disease and brain MRI …
Published in Journal of Open Source Developments · Vol. 5, Issue 3, 2018 · pp. 11–16 Read article
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Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education During COVID-19 Pandemic
Abstract: The global COVID-19 pandemic has severely affected every aspect of human life, including education. The virus' stunning spread created havoc in the educational system, causing educational institutions to close. As an effect, students must quickly adopt to the change to synchronous online learning. This study identified the different aspects affecting the adaptability level of students in online class. It also identifies the student’s adaptability level in different circumstances in online …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 1–8 Read article
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Secure Multiparty Computation for Privacy-Preserving Data Mining
Abstract: In this paper, we survey about secure multiparty computation and their importance in the field of privacy-preserving data mining. We present detailed information about defining and developing the smc protocol for privacy preserving data mining. The method of implementation of smc protocol and difficulties while demonstrating the protocol of high efficiency are reviewed. When smc protocol is applied to privacy preserving data mining, some common errors are detected. We also …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 8, Issue 3, 2021 · pp. 1–5 Read article
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A Technical Review on Intrusion Detection System with Various Machine Learning Algorithms in Data Mining
Abstract: With the progression in information & communication technology (ICT), it has become a vital element of human’s life. But this technology has brought a lot of threats in cyber world. These threats increase the chances of network vulnerabilities to attack the system in the network. To evade these attacks there are distinct ways in which one is Intrusion-Detection System (IDS). IDSs are software or hardware products that automate this monitoring …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 1, 2018 · pp. 1–8 Read article
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A Correlative Study of Machine Learning Algorithms
Abstract: Machine learning (ML) is the term used to define a systematic reading of algorithms and mathematical models of computer structure used to perform a specific task without precise programming. Learning algorithms in many programs we use every day. Nowadays, one of the reasons an online search engine like Google performs so effectively is because the learning algorithm has mastered the art of rating web sites. Additional uses for these algorithms …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 2, 2022 · pp. 30–35 Read article
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Various Approaches of Privacy Preserving in Data Mining: A Review
Abstract: AbstractData mining devices aspire to find valuable examples from vast measure of data. These patterns constitute information and are conveyed in selection trees, clusters or association rules. The information determined by the means of numerous data mining strategies can also comprise of private records approximately human beings or business. Preservation of privacy is a big thing of data mining and as a consequence has a look of attaining a few …
Published in Journal of Advanced Database Management & Systems · Vol. 4, Issue 2, 2017 · pp. 1–8 Read article
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Voting Classification Method for Network Traffic Prediction
Abstract: Prediction analysis (PA) is a data mining-based technique. The futuristic outcomes based on present data can be predicted using this technique. As the dataset is large and complex, network traffic classification is a big concern in prediction analysis. Three phases are included in network traffic strategies. The data collection is obtained in the first step of pre-processing, and it is analysed to delete incomplete and obsolete values. The relationship between …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 23–30 Read article
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Bayesian Inference to Time Series Data Mining
Abstract: The time series data mining (TSDM) framework is a fundamental contribution to the field of time series analysis and data mining in the recent past. Methods based on the TSDM framework are able to successfully characterize and predict complex, nonperiodic, irregular and chaotic time series. The TSDM methods overcome limitations including stationarity and linearity requirements of traditional time series analysis techniques by adopting data mining concepts for analyzing time series. …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 3, 2014 · pp. 10–14 Read article
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Clustering Categorical Data Using Node Importance Method
Abstract: Normal 0 false false false EN-US X-NONE X-NONE Data clustering is an important technique in data analysis. It can be defined as a given set of data objects, the problem of clustering is to partition data objects into groups in such a way that objects in same group are similar and objects in different groups are dissimilar according to the predefined similarity measurement [Han Jiawei and Kamber Micheline. Data mining: …
Published in Current Trends in Information Technology · Vol. 1, Issue 2 - 3, 2011 Read article
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Implementation of MRPrePost Parallel Algorithm based on Hadoop Platform for Large-Data Mining
Abstract: AbstractThe volume, velocity and variety of the data have increased several folds in the past few years. The conventional algorithms and techniques used to mine such huge data are found to be less efficient because these algorithms consider only the large threshold value due to which the number of candidates can be reduced, but this will lead mining association rules production to be inaccurate due to low utilization of data. …
Published in Recent Trends in Parallel Computing · Vol. 4, Issue 2, 2017 · pp. 10–20 Read article
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A Comparison Between Two Association Rule Mining Techniques
Abstract: Normal 0 false false false EN-US X-NONE X-NONE Data mining requires associated items to be mined from given transactions. Association rule mining (ARM) has gained importance in view of trend-prediction and decision-making process. Mostly ARM is implemented using variants of FP tree growth techniques. This paper introduces an improved technique for ARM – Improved Relative Dotted Sequence Path (IRDSP)-based ARM. The logic justifying why this technique saves time in comparison …
Published in Current Trends in Information Technology · Vol. 1, Issue 2 - 3, 2011 Read article
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Remote Sensing Classification Based on Improve Ant-Miner Algorithm: A Case Study of Alwar, Rajasthan, India
Abstract: Earth Observation Satellite (EOS) image itself contains image ambiguity. Various conventional methods like minimum distance to mean or maximum likelihood image clustering algorithm do not meet the accuracy that have required by user in the virtue of cost-effective land use/land cover classification. In Ant colony optimization (ACO), association rule mining is a prevalent and well researched method for discovering useful relations between variables in large databases. The proposed work presents …
Published in Journal of Geotechnical Engineering · Vol. 2, Issue 3, 2015 · pp. 1–5 Read article
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Analysis of Various Diabetes Prediction Techniques Based on Machine Learning
Abstract: AbstractData mining is a method of mine from the underdone data for maintains useful information. In organize to obtain fundamental knowledge it is important to remove bulky quantity of data. This method is consist of many important components like data cleaning, data selection, data integrity, pattern evaluation with data mining engine and database with graphical user interface. Diabetes is a chronic disease that is also known as Non‐Insulin Dependent Diabetes …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 17–22 Read article
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Improving DBSCAN using Parallel Computing Approaches
Abstract: AbstractData mining has become the buzz word of computational research due to its enormous economical and social significance. Clustering is subset of data mining operations and is a type of learning using observation techniques. Clustering uses on unsupervised learning model and does not require any training data to generate the clustering model. Clustering enables grouping of similar and dissimilar type of data in separate groups. DBSCAN is on emerging and …
Published in Recent Trends in Parallel Computing · Vol. 6, Issue 2, 2019 · pp. 20–26 Read article
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Prediction of Human Heart Disease
Abstract: AbstractData mining techniques have been widely used in clinical decision support systems for prediction and diagnosis of various diseases with good accuracy. These techniques have been very effective in designing clinical support systems because of their ability to discover hidden patterns and relationships in medical data. One of the most important applications of such systems is in diagnosis of heart diseases because it is one of the leading causes of …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 27–31 Read article
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Challenges in Individual Representation of GP Classification
Abstract: AbstractGenetic Programming (GP) is an evolutionary programming strategy that automatically solves complex problems through computer programs. The field of Data Mining has got engrossed towards GP, due to its advantages in automatic evolution of programs with optimized solutions without prior knowledge on data. The classification technique is among the most studied Data Mining task through GP. GP, despite being used for classification for long time due to its numerous outstanding …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 1, 2013 · pp. 1–4 Read article
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Data Mining Made Simple by A priori Algorithm for Market Analysis
Abstract: Data mining and data warehousing are increasingly becoming popular among IT professionals, academics and researchers from different disciplines. Business enterprises, small, medium or large scale, are considering the deployment of a warehouse as a major step and as a matter of pride. Data mining or knowledge discovery in data bases combines the techniques from mathematics, statistics, algorithms and artificial intelligence to extract the knowledge. Data mining is a main phase …
Published in Current Trends in Information Technology · Vol. 3, Issue 3, 2013 · pp. 1–4 Read article