data mining
29 articles · search the full text for this term
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Transforming Healthcare Through Big Data: Applications, Challenges, and Future Perspectives
Abstract: Healthcare institutions produce substantial amounts of information through electronic health records, laboratory systems, medical imaging technologies, patient monitoring devices, and various digital healthcare platforms. Managing and interpreting these continuously growing datasets through conventional approaches can be difficult and time-consuming. Big Data technologies offer advanced methods for storing, processing, and analyzing healthcare information efficiently, enabling healthcare professionals to obtain valuable insights for clinical and administrative purposes. This review explores the growing …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–9 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big data analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support highly informed decision-making and truly superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of BDA within the airline industry. …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 · pp. 13–18 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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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 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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Graph Theory: Its Importance and Application in Recent development of Science and Engineering
Abstract: Graph Theory is widely used in all the basic sciences including social science, due to its intrinsic simplicity it has got a lot of application in computer science, computer networks, engineering, genetics, data structure etc. Graphs are nothing but mathematical structure that helps in representing our everyday problem in a precise graphical manner. Graph Theory is the area of applied mathematics that deals with the study of objects and the …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 10, Issue 3, 2023 · pp. 31–36 Read article
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Unleashing the Power of Data Mining in Software Engineering: Applications and Case Studies
Abstract: Recent times have seen the nexus of data mining and software engineering evolve into a potent force, promising to redefine both fields. This paper highlights the critical role and varies uses of data mining within the software engineering domain, backed by the latest academic resources. The deep dive reveals critical data mining methodologies, their pertinent role across different sectors, and their unique implementations within software engineering. Various organizations, including well-known …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 3, 2023 · pp. 1–6 Read article
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An Application of Recommendation Systems to Cluster-based Pattern Recognition
Abstract: Information overload is a common problem faced by internet users; so, the recommendation system is becoming increasingly important to this service. Collective filtering is used by recommendation systems to offer recommendations to individuals or for products based on their shared interests. Data or people should be grouped into clusters so that they have more in common with those in the same cluster and stand out from those in other clusters. …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 2, 2023 · pp. 28–36 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Comparative Analysis of Algorithms for Mining Frequent Patterns
Abstract: In the computerized world, everything is moving online, and data comes in different shapes and sizes and is collected in different ways. By using data mining, frequent patterns in the databases can be identified, and it can be used in numerous applications. Finding frequent patterns in huge databases is important because it reveals important information that cannot be found through simple data surfing. To find common patterns, a variety of …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 2, 2023 · pp. 1–7 Read article
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A Latest Approach for Crime Rate Prediction and Analysis by Using the Clustering and Machine Learning Algorithm
Abstract: In our daily life, the collection and analysis of crime-related data is uncertain from a security perspective. Crime rate forecasting and analysis is a way of identifying and analyzing crime patterns in crime data contained in a crime database. Our system predicts what criminal activity occurs in everyday life in various parts of the world. Through the utilization of machine learning and data mining algorithms, it is possible to forecast …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 32–42 Read article
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Predicting the Computer Access Needs of Employee Using Data Mining Algorithms
Abstract: Every business relies on data to better organize and access the information to improve their business operations and to identify opportunities for improvement. A better framework improves the ability to valuable products and better services to their customers. The wide swaths of data that every organization gathers requires a proper methodology to gain knowledge about the latest trends in the market. Data mining is the process that analyses the data …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 1, 2023 · pp. 12–16 Read article
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Disease Prediction System Using Data Mining
Abstract: The project's main goal is to develop a system that allows users to get personalized advice on their health problems using data mining techniques. In today's hectic world, most individuals overlook this asset, which could be due to a lack of time or the intricacy of the massive data available on the internet. Our goal is to evaluate data processing techniques in clinical and health care settings in order to …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 1, 2022 · pp. 9–13 Read article
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Heart Attack Prediction System Using Machine Learning
Abstract: There is an unrestrained increase in the rate of heart strokes at puerile ages. So, there is a need to develop a system that can predict this disease at an early stage and hence preventive measures can be taken at the initial stage. It is infeasible for common people to take tests such as ECG on a regular basis and hence we require a system that is easily approachable and …
Published in Recent Trends in Programming languages · Vol. 8, Issue 2, 2021 · pp. 11–16 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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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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Privacy Enhancement on Internet of Things Using Differential Privacy Strategies
Abstract: AbstractWith recent developments in communication and data storage technologies, the Internet is gathering and storing an explosive amount of information. While such a large volume of data provides great opportunities for the exploration of knowledge, organizations do not want to share their information for legal or competitive reasons. This raises the problem of information mining while retaining privacy. Current efficient data mining privacy preservation algorithms are focused on the assumption …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 31–37 Read article
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Prediction of Likelihood of Contraceptive Method among Women using Machine Learning Techniques
Abstract: This paper presents the various machine learning techniques and early fusion approach for analyzing usage of contraceptive methods among women. The analysis has been done using various nine features that the usage of contraceptive among women is whether low, high or not at all. This paper also evaluates the effect of contraceptive prediction is affected by men, age, and religion. Finally, comparison of classification accuracy has been employed between 22 …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 6, Issue 1, 2019 · pp. 1–6 Read article