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Flexible Approach for Data Mining using Grid based Computing Concepts
2017
International Journal Of Engineering And Computer Science
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This paper discusses how distributed and Grid computing can be used to support distributed data mining. In particular, a distinction is made between distributed and Grid-based data mining methods. ...
Now days, in the field of life sciences and business, knowledge discovery has become a common task in both for the growing amount of data being gathered and for the complexity of the analysis that need ...
The Distributed Data Mining Techniques Through the growth of related data, databases in today's world are highly distributed. ...
doi:10.18535/ijecs/v6i6.26
fatcat:2t3fpjm3kfabtk6famh2i57bjm
FROM DATA MINING AND KNOWLEDGE DISCOVERY TO BIG DATA ANALYTICS AND KNOWLEDGE EXTRACTION FOR APPLICATIONS IN SCIENCE
2014
Journal of Computer Science
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Data mining" for "knowledge discovery in databases" and associated computational operations first introduced in the mid-1990 s can no longer cope with the analytical issues relating to the so-called "big ...
tools, to uncover hidden patterns, unknown correlations and other useful information lately referred to as "actionable knowledge" or "data products" from the massive volumes of complex raw data. ...
DATA MINING AND KNOWLEDGE DISCOVERY OF THE 1990 s Data mining, first introduced in the mid-1990 s, was defined as "…a step in the KDD process that consists of applying data analysis and discovery algorithms ...
doi:10.3844/jcssp.2014.2658.2665
fatcat:whtc2on6vncq5hayilctdfpvgu
Data Mining on Distributed Medical Databases: Recent Trends and Future Directions
[chapter]
2009
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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The integration needs and issues of distributed medical databases are described. Finally the paper focuses on data mining studies on distributed medical databases. ...
This paper first investigates the data mining applications on centralized medical databases, and how they are used for diagnostic and population health, then introduces distributed databases. ...
The challenge is to transform these data into information and knowledge. Data mining tools make knowledge discovery possible from these large data repositories. ...
doi:10.1007/978-3-642-03978-2_19
fatcat:ji45xofaqfbybhuh7wy5q7igo4
Domain-Driven Actionable Knowledge Discovery in the Real World
[chapter]
2006
Lecture Notes in Computer Science
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Actionable knowledge discovery is one of Grand Challenges in KDD. To this end, many methodologies have been developed. ...
However, they either view data mining as an autonomous data-driven trial-and-error process, or only analyze the issues in an isolated and case-by-case manner. ...
Introduction Actionable knowledge discovery can afford important grounds to business decision makers. ...
doi:10.1007/11731139_96
fatcat:3744kubl7jeqpoltnety3gqkdy
Data Mining Meets Grid Computing: Time to Dance?
[chapter]
2009
Data Mining Techniques in Grid Computing Environments
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Data mining (also known as knowledge discovery in databases) (Frawley, Piatetsky-Shapiro and Matheus, 1992) is a well stablished field of computer science concerned with the automated search of large volumes ...
Data mining is often described as deriving knowledge from the input data. Applying data mining to grand challenge problems brings its own computational challenges. ...
Chapter 2 is entitled 'Data analysis services in the knowledge grid'. It describes a grid-based architecture supporting distributed knowledge discovery called Knowledge Grid. ...
doi:10.1002/9780470699904.ch1
fatcat:3ax6ir5gjnhvxbnqcq5skp7a5a
Closing the Affordable Housing Gap: Identifying the Barriers Hindering the Sustainable Design and Construction of Affordable Homes
2023
Sustainability
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To identify such barriers, an exploratory data mining analysis was conducted in which agglomerative hierarchical clustering made it possible to gather latent knowledge from 3566 text-based research outputs ...
all, (2) homogeneity of provision, (3) unhealthy living environment, (4) inadequate construction project management, (5) environmental unsustainability, (6) placemaking, and (7) inadequate technical knowledge ...
knowledge discovery. ...
doi:10.3390/su15118754
fatcat:nl2uvmzad5eejku45r7pz64vry
Domain-Driven Data Mining
2006
International Journal of Data Warehousing and Mining
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Therefore, this article proposes a practical data mining methodology referred to as domain-driven data mining, which targets actionable knowledge discovery in a constrained environment for satisfying user ...
Extant data mining is based on data-driven methodologies. ...
We appreciate CMCRC and SIRCA for providing data services. Thanks also go to Dr. Lin Li and Jiarui Ni for implementation supports. ...
doi:10.4018/jdwm.2006100103
fatcat:wk465g5n5zesrn2srxeoslb7py
Providing Decision Support for the Condition-Based Maintenance of Circuit Breakers Through Data Mining of Trip Coil Current Signatures
2007
IEEE Transactions on Power Delivery
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This paper proposes a data mining method for the analysis of condition monitoring data, and demonstrates this method in its discovery of useful knowledge from trip coil data captured from a population ...
2007) Providing decision support for the condition-based maintenance of circuit breakers through data mining of trip coil current signatures. ...
Data mining may therefore be considered a knowledge extraction process aimed at "making sense" of large data sets through the discovery of hidden and often unsuspected facts, patterns and correlations ...
doi:10.1109/tpwrd.2006.883001
fatcat:2pkxuxn4qjdp7nrukewlkggmd4
Benefits of Using Data Mining Techniques for Business Intelligence
2022
Journal of Research in Science and Engineering
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The outcome of research shows that data mining tools are capable of discovering patterns in data in few hours those expert human quantitative analysts might not find in years of work to help make decision ...
This paper is discussing data mining techniques and business operations areas includes marketing, finance, fraud detection, manufacturing, telecommunication to improve their business and found excellent ...
Data Mining Techniques Various data mining techniques used for business development are Classification, Regression, Clustering, Summarization, Association Rules, Genetic algorithm used for knowledge discovery ...
doi:10.53469/jrse.2022.04(07).09
fatcat:jprcfyjtnbeppmtlw53bonz3je
Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks
2018
International Journal of Data Mining Techniques and Applications
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Knowledge discovery and data mining have found numerous applications in business and scientific domain. ...
Valuable knowledge can be discovered from application of data mining techniques in healthcare system. ...
Data mining is the core step, which results in the discovery of hidden but useful knowledge from massive databases. ...
doi:10.20894/ijdmta.102.007.001.027
fatcat:22rynqjrdjc67nbrxeljsvdc2a
Multidimensional Data Analysis, Data Mining and Knowledge Discovery
2024
Zenodo
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Keywords:- Data, Mining, Data Mining, Multidimensional Data Analysis, Knowledge Data Discovery. ...
Our work further highlighted the current and future trends in data mining and the numerous positives of multidimensional data analysis/data mining and knowledge discovery to individuals, organizations, ...
It is also referred to as knowledge discovery process, knowledge mining data, knowledge extraction, multidimensional data analysis or data /pattern analysis. ...
doi:10.5281/zenodo.10656236
fatcat:42dbavuxofejvc3ldoy37srw5e
An integrative framework for knowledge extraction in collaborative virtual environments
2001
Proceedings of the 2001 International ACM SIGGROUP Conference on Supporting Group Work - GROUP '01
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The paper presents a framework for integrating knowledge discovery techniques with collaborative virtual environments, starting from early conceptual development. ...
The aim of this research is to utilize this data effectively, extract meaningful insights out of it and feeding discovered knowledge back into the environment. ...
Knowledge discovery starts with applying traditional data mining algorithms to collaboration data leading to the discovery of patterns in the data. ...
doi:10.1145/500286.500298
dblp:conf/group/Biuk-AghaiS01
fatcat:tjqnuqpuvffmbkfbanivqefbxi
An integrative framework for knowledge extraction in collaborative virtual environments
2001
Proceedings of the 2001 International ACM SIGGROUP Conference on Supporting Group Work - GROUP '01
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The paper presents a framework for integrating knowledge discovery techniques with collaborative virtual environments, starting from early conceptual development. ...
The aim of this research is to utilize this data effectively, extract meaningful insights out of it and feeding discovered knowledge back into the environment. ...
Knowledge discovery starts with applying traditional data mining algorithms to collaboration data leading to the discovery of patterns in the data. ...
doi:10.1145/500294.500298
fatcat:vq2x5gttufcgpellaqieymz27u
The affordance of virtual reality to enable the sensory representation of multi-dimensional data for immersive analytics: from experience to insight
2018
Journal of Big Data
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part of the more general process known as Knowledge Discovery in Databases. ...
The insight may be undertaken solely through human interaction with data visualizations, or be undertaken in a hybrid approach where data mining algorithms are combined with interactive visualization. ...
Abbreviations CAVE: computer aided virtual environment; EDA: exploratory data analysis; HCI: human computer interfaces; HMD: head mounted display; VR: virtual reality; VDM: visual data mining. ...
doi:10.1186/s40537-018-0158-z
fatcat:76o37al2lvfnrccazuegiwpmri
Surveying the complementary role of automatic data analysis and visualization in knowledge discovery
2009
Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery Integrating Automated Analysis with Interactive Exploration - KDD '09
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The aim of this work is to survey and reflect on the various ways to integrate visualization and data mining techniques toward a mixed-initiative knowledge discovery taking the best of human and machine ...
data mining employ infovis techniques. ...
CONCLUSIONS We have presented a literature review on the role of visualization and data mining in the knowledge discovery process. ...
doi:10.1145/1562849.1562851
dblp:conf/kdd/BertiniL09
fatcat:qqrfxgbn6fftpcpooralhd5h6i
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