1. Top 50 Research Papers in Time-Series Data Mining

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  2. (PDF) Educational Data Mining: a Case Study

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  3. 😍 Data mining research paper. What are some good research topics in

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  5. (PDF) Big Data with Data Mining

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  6. (PDF) Based on Data Mining Algorithm of Data Mining Research

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  1. Major Issues in Data Mining || Data Mining challenges

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  1. data mining Latest Research Papers

    Epidemic diseases can be extremely dangerous with its hazarding influences. They may have negative effects on economies, businesses, environment, humans, and workforce. In this paper, some of the factors that are interrelated with COVID-19 pandemic have been examined using data mining methodologies and approaches.

  2. Data mining

    Data mining is the process of extracting potentially useful information from data sets. It uses a suite of methods to organise, examine and combine large data sets, including machine learning ...

  3. Home

    Overview. Data Mining and Knowledge Discovery is a leading technical journal focusing on the extraction of information from vast databases. Publishes original research papers and practice in data mining and knowledge discovery. Provides surveys and tutorials of important areas and techniques. Offers detailed descriptions of significant ...

  4. 345193 PDFs

    Explore the latest full-text research PDFs, articles, conference papers, preprints and more on DATA MINING. Find methods information, sources, references or conduct a literature review on DATA MINING

  5. Knowledge Discovery: Methods from data mining and machine learning

    Abstract. The interdisciplinary field of knowledge discovery and data mining emerged from a necessity of big data requiring new analytical methods beyond the traditional statistical approaches to discover new knowledge from the data mine. This emergent approach is a dialectic research process that is both deductive and inductive.

  6. Recent Advances in Data Mining

    Data mining is the procedure of identifying valid, potentially suitable, and understandable information; detecting patterns; building knowledge graphs; and finding anomalies and relationships in big data with Artificial-Intelligence-enabled IoT (AIoT). This process is essential for advancing knowledge in various fields dealing with raw data ...

  7. Recent advances in domain-driven data mining

    Data mining research has been significantly motivated by and benefited from real-world applications in novel domains. This special issue was proposed and edited to draw attention to domain-driven data mining and disseminate research in foundations, frameworks, and applications for data-driven and actionable knowledge discovery. Along with this special issue, we also organized a related ...

  8. Data mining

    Read the latest Research articles in Data mining from Scientific Reports. ... Identifying and overcoming COVID-19 vaccination impediments using Bayesian data mining techniques ... Calls for Papers ...

  9. A comprehensive survey of clustering algorithms: State-of-the-art

    This survey is intended to provide a convenient research path for new researchers, furnishing them with a comprehensive study on the various data clustering techniques and research progression over the years in clustering techniques. ... The paper surveyed the different data mining methods that can be applied to extract knowledge about multi ...

  10. Articles

    Alexander Bertrand. Correction 02 January 2024 Pages: 652 - 652. 1. 2. …. 24. Next. Data Mining and Knowledge Discovery is a leading technical journal focusing on the extraction of information from vast databases. Publishes original research ...

  11. (PDF) Trends in data mining research: A two-decade review using topic

    Address: 20, Myasnitskaya Street, Moscow 101000, Russia. Abstract. This work analyzes the intellectual structure of data mining as a scientific discipline. T o do this, we use. topic analysis ...

  12. Data mining techniques and applications

    This paper reviews data mining techniques and its applications such as educational data mining (EDM), finance, commerce, life sciences and medical etc. We group existing approaches to determine how the data mining can be used in different fields. Our categorization specifically focuses on the research that has been published over the period ...

  13. Data Mining in Healthcare: Applying Strategic Intelligence Techniques

    Exploration of data mining and machine learning in public health sector. 2011-2019: Investigation of medical data mining using VOSviewer and CiteSpace software. This paper: 1995-2020: A BPNA of data mining in healthcare: performance analysis, strategic themes, thematic evolution structure, trends and future opportunities using SciMAT software.

  14. Data Mining for the Internet of Things: Literature Review and

    Nowadays, big data is a hot topic for data mining and IoT; we also discuss the new characteristics of big data and analyze the challenges in data extracting, data mining algorithms, and data mining system area. Based on the survey of the current research, a suggested big data mining system is proposed.

  15. Data mining in clinical big data: the frequently used databases, steps

    Data mining is a multidisciplinary field at the intersection of database technology, statistics, ML, and pattern recognition that profits from all these disciplines [].Although this approach is not yet widespread in the field of medical research, several studies have demonstrated the promise of data mining in building disease-prediction models, assessing patient risk, and helping physicians ...

  16. Data Mining and Modeling

    Data mining lies at the heart of many of these questions, and the research done at Google is at the forefront of the field. Whether it is finding more efficient algorithms for working with massive data sets, developing privacy-preserving methods for classification, or designing new machine learning approaches, our group continues to push the ...

  17. Mining Big Data in Education: Affordances and Challenges

    A broad range of data mining techniques can be utilized for big data in education, which Baker and Siemens (2014) broadly categorize into prediction methods, including inferential methods that model knowledge as it changes; structure discovery algorithms, with emphasis on discovering the structures of content and skills in an educational domain and the structures of social networks of learners ...

  18. (PDF) A Review of Data Mining Literature

    REVIEW OF LITERATURE. Fayyad (1996) [3] in their paper " From data mining. to knowledge discovery in databases" desc ribed KDD. as "a nontrivial proce ss of recognizing valid, novel ...

  19. Data Mining

    Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. ... We propose a new unsupervised machine learning technique, denominated as Trace-based clustering, and a 5-step methodology in order to support clinicians when identifying patient phenotypes. ... is a supervised data mining ...

  20. Review Paper on Data Mining Techniques and Applications

    Abstract. Data mining is the process of extracting hidden and useful patterns and information from data. Data mining is a new technology that helps businesses to predict future trends and behaviors, allowing them to make proactive, knowledge driven decisions. The aim of this paper is to show the process of data mining and how it can help ...

  21. The plan to mine the world's research papers

    The power of data mining. The JNU data store could sweep aside barriers that still deter scientists from using software to analyse research, says Max Häussler, a bioinformatics researcher at the ...

  22. Data mining

    Mountainous amounts of data records are now available in science, business, industry and many other areas. Such data can provide a rich resource for knowledge discovery and decision support. Data mining is the process of identifying interesting patterns from large databases. Data mining is the core part of the knowledge discovery in database (KDD) process. The KDD process may consist of the ...

  23. Link prediction in directed complex networks: combining similarity

    Discovering new relationships between entities in networked data is essential in various applications such as sociology, security, physics, and biology. This paper introduces a novel approach to directed link prediction, filling a notable research gap by acknowledging the importance of the directionality of relationships often overlooked in traditional methods. We present three algorithms: an ...

  24. Article: Access controllable multi-blockchain platform for enterprise R

    Effective management of their precipitated data and safe sharing of data can improve the collaboration efficiency of research and development personnel, which has become the top priority of enterprise development. This paper proposes to use blockchain technology to assist the collaboration efficiency of enterprise R&D personnel.

  25. Healthcare Analytics Information, News and Tips

    White Papers; Sponsored Sites; Follow: ... Electronic phenotyping has significant potential to drive EHR-based data mining and clinical research, but patient privacy remains a major concern. View All The Latest News. Insights. ... Six new data dashboards will track cancer, care access and SDOH across South Carolina's 46 counties in an effort ...

  26. (PDF) Data mining techniques and applications

    Only those papers that were published in the area of data mining were focused on this research. Between 1995 and 2021, 34,011 works were discovered that were published in too many different ...

  27. Research on Taxi Demand Prediction Based on Deep Learning and Multi

    This research utilizes deep learning to comprehensively forecast taxi demand in New York City and designs both regional and city-wide modules, overcoming the limitations of focusing on small areas and ignoring the heterogeneity among urban regions. Accurate prediction of taxi demand is crucial for the decision-making process of ride-hailing platforms. Many studies are limited to small-scale ...