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Data Mining and Knowledge Discovery
[chapter]
1998
Data Mining Methods for Knowledge Discovery
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In this paper, a review study is done on existing data mining and knowledge discovery techniques, applications and process models that are applicable to healthcare environments. ...
Knowledge Discovery in Databases (KDD) can help organizations turn their data into information. ...
A proper medical database created with intention mining can provide a useful resource for data mining and knowledge discovery [1] . ...
doi:10.1007/978-1-4615-5589-6_1
fatcat:p2oyvrwv6rdxlam7jtunbsz56q
Data Mining and Knowledge Discovery
[chapter]
2021
The Urban Book Series
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We study the empirical performance of these methods and demonstrate how data-mining techniques can be successfully applied to social-sensing data to extract actionable knowledge and facilitate downstream ...
In this chapter, we present recent developments in data-mining techniques for urban activity modeling, a fundamental task for extracting useful urban knowledge from social-sensing data. ...
Data Mining for Urban Analysis Generally, data-mining techniques for urban analysis tasks can be categorized into four classes: (1) urban pattern discovery; (2) urban activity modeling; (3) urban mobility ...
doi:10.1007/978-981-15-8983-6_42
fatcat:gxnx3jgu4fcqvbieg3ltmdovk4
Knowledge Discovery and Data Mining
2020
International Journal for Research in Applied Science and Engineering Technology
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knowledge discovery in databases (KDD) plays an important role in large organisation where data is store in large base.it help with exploring and understanding very large data set and building predictive ...
This is the task-oriented process it been to identifying valid useful and understandable pattern from large and complex data set .data mining is the core of KDD process in KDD process interring the algorithm ...
means knowledge discovery in database. ...
doi:10.22214/ijraset.2020.32045
fatcat:2tj5wei5vfantdzjr3jwog4uhi
Biological Knowledge Discovery and Data Mining
2012
Scientific Programming
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discovery and data mining (KDD) processes are playing increasingly important roles. ...
The ongoing influx of these data, the inherent uncertainties in data collection processes, and the gap between data collection and knowledge curation have created exciting opportunities for data mining ...
doi:10.1155/2012/252681
fatcat:qmbadw7brfdjjigtrakhebhz74
Big Data Mining and Knowledge Discovery
2016
Journal of Communications Technology Electronics and Computer Science
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The article dealt with exploration methods and tools for big data. It identifies the challenges encountered in the analysis of big data. ...
Defined notion of big data. describe the technology for big data analysis. Article provides an overview of tools which are designed for big data analytics. ...
THE DATA MINING IN ERA OF BIG DATA Big data mean those data sets, which become quite difficult or impossible to hadle by using simple data-processing programs and tools because of their size and complex ...
doi:10.22385/jctecs.v9i0.134
fatcat:5tpz6gfqsbgbbi3t23np75ubwy
Statistical Data Mining and Knowledge Discovery
2004
Technometrics
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The use of automated indexing and text mining can revolutionize the manner and speed of information assessment and organization. ...
All punctuation and capitalization is ignored. In addition, articles and other common, non-distinguishing words are discarded. ...
doi:10.1198/tech.2004.s762
fatcat:vpwc3p3ru5f6vnd5vw2zhhjefy
Geographic Data Mining and Knowledge Discovery An Overview
[chapter]
2009
Geographic Data Mining and Knowledge Discovery, Second Edition
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KNOWLEDGE DISCOVERY AND DATA MINING In this section of the chapter, we provide a general overview of knowledge discovery and data mining. ...
In this chapter, we provide an overview of knowledge discovery from databases (KDD) and data mining. ...
Acknowledgments: Thanks to Mark Gahegan and Phoebe McNeally for some helpful comments on this chapter. ...
doi:10.1201/9781420073980.ch1
fatcat:bfh4kasvlbhylgwu2afp5wrqbq
Data mining and knowledge discovery in databases
1996
Communications of the ACM
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Data Mining to etap procesu odkrywania wiedzy w bazach danych (Knowledge Discovery Process in Databases, KDD Process), w którym analizuje siê dane i dostarcza wzorce i modele z tych danych 1 . ...
Pojêcie Data Mining nie jest obce statystykom. ...
Friedman, op.cit. 31 Introduction to Data Mining and Knowledge Discovery -2 nd edition, The Two Crows Corporation 1998, tekst pobrano ze strony www.twocrows.com
Rys. 1. ...
doi:10.1145/240455.240463
fatcat:axaz4jiytrgybp434jpyrredtm
Advances in knowledge discovery and data mining
1996
Computers and Mathematics with Applications
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General implications and applications. ...
Creative visualization. fixation, and incubation. References. Index. Introduction to creative cognition. 2. Theoretical and methodological considerations. 4. Creative invention. 5. ...
From data mining to knowledge discovery: An overview (Usama M. Fayyad, Gregory Piatetsky-Shapiro and Padhraic Smyth). 1. Foundations. 2. ...
doi:10.1016/s0898-1221(96)90007-3
fatcat:kmpq3mv5evc75f2ifvbwdn5jjq
A Data Mining & Knowledge Discovery Process Model
[chapter]
2009
Data Mining and Knowledge Discovery in Real Life Applications
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Data Mining & Knowledge Discovery Process Model ...
Introduction The number of applied in the data mining and knowledge discovery (DM & KD) projects has increased enormously over the past few years (Jaffarian et al., 2008) (Kdnuggets.com, 2007c) . ...
applications of data mining in different promising areas like Industrialist, Biological, and Social. ...
doi:10.5772/6438
fatcat:7bvdr6n4gfabpnlnb5g2ud43be
Toward knowledge-rich data mining
2007
Data mining and knowledge discovery
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This position paper proposes knowledge-rich data mining as a focus of research, and describes initial steps in pursuing it. ...
In sum, data mining as practiced today is mostly knowledge-poor; current tools do not facilitate the incorporation and reuse of knowledge, and this is perhaps the single greatest barrier to progress. ...
Because of the knowledge it can draw on, a data mining system will be able to discover deeper patterns, and directly connect them to the actions that should result. ...
doi:10.1007/s10618-007-0069-7
fatcat:viajhww3lvbexpdnvmvlkowg4e
DATA SCIENCE AND KNOWLEDGE DISCOVERY THROUGH DATA MINING PARADIGMS
2019
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES
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On the flip side of the coin, the development of intellectual and evolutionary data mining tool for retail industries through the machine learning algorithm has always been proved to adequately respond ...
Customer behavior analysis and its knowledge have always been given its due importance in research community to develop real life practical solutions. ...
Association
ISSN (Online) : 2454 -7190 ISSN (Print) 0973-8975 rule mining is an active research area with numerous algorithms used for knowledge discovery. ...
doi:10.26782/jmcms.2019.04.00014
fatcat:5yffofrsozelnle4ksdf5e6rfm
Multimedia Data Mining
[chapter]
2009
Data Mining and Knowledge Discovery Handbook
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interaction, machine learning, statistical modeling, data
mining, pattern analysis, data fusion, social sciences, and domain knowledge
for applications
Motivations (3)
8
I. ...
Faloutsos, and P. Duygulu. Automatic Multimedia Cross-modal Correlation Discovery. KDDM'04, 2004 [RHO+98] Y. Rui, T.S. Huang, M. Ortega, and S. ...
doi:10.1007/978-0-387-09823-4_57
fatcat:cnrw7f656rcmvjlbdw3yg453xy
Mining High-Dimensional Data
[chapter]
2009
Data Mining and Knowledge Discovery Handbook
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In this chapter, we present several state-of-art techniques for analyzing highdimensional data, e.g., frequent pattern mining, clustering, and classification. ...
Thus, mining highdimensional data is an urgent problem of great practical importance. ...
Researchers and practitioners are very eager in analyzing these data sets. Various data mining models have been proven to be very successful for analyzing very large data sets. ...
doi:10.1007/978-0-387-09823-4_41
fatcat:lujokq34q5d6tde53kmlhj2c7u
Data Stream Mining
[chapter]
2009
Data Mining and Knowledge Discovery Handbook
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Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. ...
MOA is related to WEKA, the Waikato Environment for Knowledge Analysis, which is an award-winning open-source workbench containing implementations of a wide range of batch machine learning methods. ...
data mining. ...
doi:10.1007/978-0-387-09823-4_39
fatcat:3n27k753zzhidbkjynx7iwmt7e
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