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Data Mining Introduction
Data mining Challenges
what is data mining and what are its challenges
Applications and Trends in Data Mining
Stages of Data Mining: From Problem to Deployment
COMMENTS
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.
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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
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 ...
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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 ...
(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 ...
(PDF) Trends in data mining research: A two-decade review using topic
The research direction related to practical Applications of data mining also shows a tendency to grow. The last two topics, Text Mining and Data Streams have attracted steady interest from ...
Data Mining for the Internet of Things: Literature Review and
A variety of researches focusing on knowledge view, technique view, and application view can be found in the literature. However, no previous effort has been made to review the different views of data mining in a systematic way, especially in nowadays big data [5-7]; mobile internet and Internet of Things [8-10] grow rapidly and some data mining researchers shift their attention from data ...
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 ...
Data mining
Analysis and visualisation of electronic health records data to identify undiagnosed patients with rare genetic diseases. Daniel Moynihan. , Sean Monaco. & Saumya Shekhar Jamuar. Article. 21 ...
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 ...
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 ...
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.
A comprehensive survey of data mining
Data mining plays an important role in various human activities because it extracts the unknown useful patterns (or knowledge). Due to its capabilities, data mining become an essential task in large number of application domains such as banking, retail, medical, insurance, bioinformatics, etc. To take a holistic view of the research trends in the area of data mining, a comprehensive survey is ...
Adaptations of data mining methodologies: a systematic literature
The main research objective of this article is to study how data mining methodologies are applied by researchers and practitioners. To this end, we use systematic literature review (SLR) as scientific method for two reasons. Firstly, systematic review is based on trustworthy, rigorous, and auditable methodology.
Data Mining in Healthcare: Applying Strategic Intelligence Techniques
The Computer Science's themes related to data mining and the medical research concepts, depicted, respectively, in the grey and blue areas of the thematic evolution diagram (Figure 6), demonstrates the evolution of the research field over the different sub-periods addressed in this study. In this way, each individual theme relevance is ...
Data Mining Research
Data mining is defined as the process of discovering hidden and potentially useful information from very large databases [4].The progress in data mining research has made it possible to implement several data mining operations efficiently on large databases. While this is surely an important contribution, we should not lose sight of the final goal of data mining - it is to enable database ...
Data Mining and Modeling
Data Mining and Modeling. The proliferation of machine learning means that learned classifiers lie at the core of many products across Google. However, questions in practice are rarely so clean as to just to use an out-of-the-box algorithm. A big challenge is in developing metrics, designing experimental methodologies, and modeling the space to ...
Data Mining
Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. ... (SD) is a supervised data mining technique for identifying a set of relations (subgroups) among attributes from a dataset with respect to a target attribute. ... Papers With Code is a free resource with all data licensed under ...
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 ...
Systematic Review of Machine Learning Applications in Mining ...
Recent developments in smart mining technology have enabled the production, collection, and sharing of a large amount of data in real time. Therefore, research employing machine learning (ML) that utilizes these data is being actively conducted in the mining industry. In this study, we reviewed 109 research papers, published over the past decade, that discuss ML techniques for mineral ...
(PDF) A Review of Data Mining Literature
REVIEW OF LITERATURE. Fayyad et.al (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 ...
Top 10 Data Mining Papers: Recommended Reading
Research in data mining continues growing in business and in learning organization over coming decades. This review paper explores the applications of data mining techniques which have been developed to support knowledge management process. The journal articles indexed in ScienceDirect Database from 2007 to 2012 are analyzed and classified ...
Article: Application of digital twin virtual design and BIM technology
Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.
Sparrows as sentinels: Health study illustrates the interconnectedness
Then, they compared lead levels from those samples to data from a 30-year child blood lead monitoring program, finding a strong relationship between the two datasets across all of the sites sampled. For example, levels in both sparrows and children were higher near the mining sites and declined similarly as distance from the mining sites increased.
(PDF) DATA MINING IN HEALTHCARE
Data mining is a powerful new tec hnology with gr eat potential t o help c ompanies. focus on the m ost important information in the data they have collected about the behavior. of their customers ...
Over half of global mines and their impacts are undocumented: Paper
There is a lack of publicly available data on mine production, waste, pollution and water and energy consumption, a recent commentary published in the journal Nature has highlighted. More than half of the global mining areas (56 per cent) visible from satellite images have no production information listed, raising concerns about their mostly unmeasured environmental and social consequences ...
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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.
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
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 ...
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 ...
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 ...
The research direction related to practical Applications of data mining also shows a tendency to grow. The last two topics, Text Mining and Data Streams have attracted steady interest from ...
A variety of researches focusing on knowledge view, technique view, and application view can be found in the literature. However, no previous effort has been made to review the different views of data mining in a systematic way, especially in nowadays big data [5-7]; mobile internet and Internet of Things [8-10] grow rapidly and some data mining researchers shift their attention from data ...
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 ...
Analysis and visualisation of electronic health records data to identify undiagnosed patients with rare genetic diseases. Daniel Moynihan. , Sean Monaco. & Saumya Shekhar Jamuar. Article. 21 ...
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 ...
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 ...
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.
Data mining plays an important role in various human activities because it extracts the unknown useful patterns (or knowledge). Due to its capabilities, data mining become an essential task in large number of application domains such as banking, retail, medical, insurance, bioinformatics, etc. To take a holistic view of the research trends in the area of data mining, a comprehensive survey is ...
The main research objective of this article is to study how data mining methodologies are applied by researchers and practitioners. To this end, we use systematic literature review (SLR) as scientific method for two reasons. Firstly, systematic review is based on trustworthy, rigorous, and auditable methodology.
The Computer Science's themes related to data mining and the medical research concepts, depicted, respectively, in the grey and blue areas of the thematic evolution diagram (Figure 6), demonstrates the evolution of the research field over the different sub-periods addressed in this study. In this way, each individual theme relevance is ...
Data mining is defined as the process of discovering hidden and potentially useful information from very large databases [4].The progress in data mining research has made it possible to implement several data mining operations efficiently on large databases. While this is surely an important contribution, we should not lose sight of the final goal of data mining - it is to enable database ...
Data Mining and Modeling. The proliferation of machine learning means that learned classifiers lie at the core of many products across Google. However, questions in practice are rarely so clean as to just to use an out-of-the-box algorithm. A big challenge is in developing metrics, designing experimental methodologies, and modeling the space to ...
Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. ... (SD) is a supervised data mining technique for identifying a set of relations (subgroups) among attributes from a dataset with respect to a target attribute. ... Papers With Code is a free resource with all data licensed under ...
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 ...
Recent developments in smart mining technology have enabled the production, collection, and sharing of a large amount of data in real time. Therefore, research employing machine learning (ML) that utilizes these data is being actively conducted in the mining industry. In this study, we reviewed 109 research papers, published over the past decade, that discuss ML techniques for mineral ...
REVIEW OF LITERATURE. Fayyad et.al (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 ...
Research in data mining continues growing in business and in learning organization over coming decades. This review paper explores the applications of data mining techniques which have been developed to support knowledge management process. The journal articles indexed in ScienceDirect Database from 2007 to 2012 are analyzed and classified ...
Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.
Then, they compared lead levels from those samples to data from a 30-year child blood lead monitoring program, finding a strong relationship between the two datasets across all of the sites sampled. For example, levels in both sparrows and children were higher near the mining sites and declined similarly as distance from the mining sites increased.
Data mining is a powerful new tec hnology with gr eat potential t o help c ompanies. focus on the m ost important information in the data they have collected about the behavior. of their customers ...
There is a lack of publicly available data on mine production, waste, pollution and water and energy consumption, a recent commentary published in the journal Nature has highlighted. More than half of the global mining areas (56 per cent) visible from satellite images have no production information listed, raising concerns about their mostly unmeasured environmental and social consequences ...