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129 articles for “Data mining Technique”
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Enhancing Pattern Recognition in Social Networking Dataset using Data Mining Techniques
Abstract: Databases today can range in size more than terabytes. Within these masses of data lies hidden information of strategic importance. But when there are so many trees, how do we draw meaningful conclusions about the forest? The newest answer is data mining, which is being used both to increase revenues and to reduce costs. Data mining is a process that uses a variety of data analysis tools to discover patterns …
Published in Journal Of Network security · Vol. 1, Issue 2-3, 2013 · pp. 1–7 Read article
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Predicting Employees Performance using Data Mining Techniques
Abstract: Human resources management (HRM) has become one of the essential interests of managers and 4decision-makers in almost all types of businesses to adopt plans for correctly discovering highly qualified employees. In this research, data mining techniques were utilized to build a classification model for predicting the performance of employees using a real dataset. For this, we are using different methods such as support vector machine, Logistic Regression and Neural Network. …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 1, 2021 · pp. 4–13 Read article
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Data Mining Techniques Used in Prediction of Heart Diseases
Abstract: AbstractHeart disease is a big life minatory ailment that cause to demise. It has deep long-term incompetence. There is a huge amount of data available within our system. Nevertheless, we are unable to find hidden relationship and prosperity in data. KDD (knowledge discovery in database) process, data mining consists of various techniques to convert these mounds of data into useful decision-making information. Data mining takes less time for the prediction …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 3, 2019 · pp. 9–11 Read article
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Making World as More Green and Healthy using Data Mining Techniques
Abstract: AbstractTrees are vital. As the biggest plants on the planet, they give us oxygen, store carbon, stabilize the soil and give life to the world's wildlife. A study from 2017 reveals the information that more than 150 acres lost every minute of every day, and 78 million acres lost every year, yet there is no proper technical solution to identify the places of deforestation and to plant trees on those …
Published in Journal of Computer Technology & Applications · Vol. 10, Issue 1, 2019 · pp. 17–22 Read article
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Disease Prediction for Heart using Data Mining Techniques and Decision Tree Classification
Abstract: Heart disease is a prominent cause of death worldwide, and many people are concerned about it. Early detection of heart disease becomes very crucial and has the potential to save many lives. However, detecting cardiovascular diseases such as heart attacks, coronary artery disease, and others of similar types is a critical challenge presented by routine clinical data analysis, even by using well known algorithms. We can’t risk lives of people …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 16–22 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Various Techniques of Data Mining in Social Network Mining: Review
Abstract: AbstractIn recent trends, social network has gained a large boom and the companies are using the social network mining as a tool for getting profit in their business. They are using different data mining techniques which we have covered in this study. We have also given a comparative study on how different data mining techniques are being used by them. Keywords: Social network mining, data mining, SVM, Bayesian networkCite this …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 2, 2019 · pp. 8–11 Read article
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A Survey Paper on Gene Expression Data in Data Mining
Abstract: For analyzing the gene expression data, data mining technique, i.e. data clustering methods are to be more victorious. Cluster analyses are performed to look for separating the given data set into groups that are based on particular characteristics or behavior;therefore the data are much similar in the same group and different from other cluster/groups. From past few decades, various studies on cluster analysis have been developed. Most traditional clustering algorithms …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 1, 2017 · pp. 14–22 Read article
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A Study on Privacy Preserving Techniques in Data Mining
Abstract: Data Mining (DM) is the technique of examining data from specific summarizing and perspectives the outcome as useful information. It has been describing as "the non-trivial procedure of new, potentially helpful and ultimately conceivable patterns and identifying valid in data". The word “Knowledge” in KDD submits to the discovery of example which is removing since the processed data. Preserving privacy is becoming a key apprehension as personal data is publicly …
Published in Journal of Operating Systems Development & Trends · Vol. 5, Issue 2, 2018 · pp. 18–23 Read article
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Breast Cancer Diagnosis Using Data Mining Classification Techniques Using Weka
Abstract: Breast cancer is currently posing a serious threat and is the second leading cause of death in women. A good and accurate diagnosis is important in order to control the very high recurrence rate of breast cancer. In this work, we explore the applicability of various data mining classifier to predict the presence of breast cancer. The performance of conventional supervised learning algorithms such as NaïveBayes, J4.8, SMO, IBk and …
Published in Recent Trends in Programming languages · Vol. 4, Issue 3, 2017 · pp. 7–15 Read article
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A Detailed Survey on Crime Detecting and Clustering Technique in Data Mining
Abstract: AbstractData mining is the extraction of useful information or the knowledge from the set of data or it’s the process analyzing the data from the various perspectives and summarizing into information which is useful. Detection of crime begins with discovery of crime scene, and proceeds from side to side the process of evidence collected works, identification and the analysis. It is called as an act that is being committed or …
Published in Journal of Advanced Database Management & Systems · Vol. 4, Issue 2, 2017 · pp. 19–26 Read article
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Design and Development of Automatic and Effective Bug Triaging Technique using Data Mining
Abstract: Bug fixing is an important task in bug triaging which aims the assignment of a new bug to the correct developer. The automatic bug triage is used to reduce the time and cost in manual work. In this paper, we focus on different modules and the result is produced by the user module. User is the person who creates the account and fixes the bug assigned to him.Keywords: Bug triage, …
Published in Journal of Web Engineering & Technology · Vol. 3, Issue 1, 2016 · pp. 1–6 Read article
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A Methdology of Software Cost Estimation Techniques for Data Mining
Abstract: Many software projects fail every year due to increasing size and complexity of software projects. To deal with this problem many researcher have been focused on this area of Cost estimation since 1960s. The cost estimation is usually dependent upon the size estimate of the project, which may use lines of code as metrics. Software engineering plays an important role in software development process. It is used to develop quality …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 2, 2018 · pp. 82–87 Read article
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Novel Algorithm for Finding the Range of Fuzzy Values for Quantitative Data Sets by Data Mining and Fuzzy Technique
Abstract: We all know, when we have large data sets, then applying data mining association rule is difficult. Fuzzy based classification technique is to overcome above problem. This technique divides the large data sets in two parts. First part carries useful data sets and second part applies data mining association algorithm. We can also be able to find the frequent classes or frequent fuzzy values of quantitative data sets. We also …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 1, 2015 · pp. 27–32 Read article
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A Review Paper Based on Methodologies and Applications of Data Mining
Abstract: Data mining is like extracting record from a heap of data. Understanding database concepts is vital for data mining. Knowledge Discovery in Databases (KDD) is used to discover crucial data-related information. Our motive is being inundated with exceptional types of information science statistics, environmental records, financial records, and mathematical records. Summarizing the information manually is not possible because of the notable data boom inside the age of community and records …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 3, 2022 · pp. 8–15 Read article
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Autism Spectrum Disorder Prediction Using Classification Techniques: A Comparative Analysis
Abstract: Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder marked by difficulties in social interaction, communication, and repetitive behaviors. Identifying and addressing ASD early is essential for enhancing the quality of life for those affected. Data mining techniques have emerged as powerful tools in analyzing large datasets to predict and diagnose ASD, aiding in early identification and intervention. This article presents a comprehensive comparative analysis of classification techniques employed in …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 66–71 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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A Survey on Genetic Programming in Data Mining Tasks
Abstract: ABSTRACTGenetic programming (GP) is a machine learning technique used to give the optimized solution for the user specified tasks from a population of computer programs based on a fitness function. Genetic programming provides automated and optimized solutions for searching of large, poorly defined search spaces and even with the complexities of high dimensionality, multi-modality and discontinuity with noise. Knowledge discovery is an extremely complex process in the real world databases. …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 1, 2012 · pp. 9–15 Read article
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A Survey on Datamining Techniques and its Uses on Real-Time Applications
Abstract: AbstractData mining is one of the area gaining lot of sensible significance and is progressing at a brisk pace with new methods, methodologies and findings in diverse packages associated with remedy, computer science, bioinformatics and stock market prediction, climate forecast, textual content, audio and video processing to name a few. Data occurs to be the key difficulty in statistics mining. With the massive online facts generated from several sensors, Internet …
Published in Journal of Open Source Developments · Vol. 7, Issue 3, 2020 · pp. 12–17 Read article
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Comparative Analysis of algorithms for Credit Card Fraud Detection using Data Mining: A Review
Abstract: AbstractData mining is a technique to extract new useful information from existing dataset. It is used to predict various patterns from present dataset. It has a great application in the field of bank and finance. In today’s world, everything is being online, means online shopping, online banking and online payment. The problem faced by them is credit card fraud. In this, we use the data mining techniques such as classification, …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 2, 2019 · pp. 12–17 Read article