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Database Issues in Knowledge Discovery and Data Mining
1999
Australasian Journal of Information Systems
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The terms "Knowledge Discovery in Databases" and "Data Mining" have been adopted for a field of research dealing with the automatic discovery of knowledge impb'cit within databases. ...
, the different types of discovered knowledge, the way knowledge discovery systems operate on different data types, various techniques for knowledge discovery and the ways in which discovered knowledge ...
The term Data Mining, or Knowledge Discovery in Databases (KDD), has been adopted for a field of research dealing with the discovery of information or knowledge from data held in more or less structured ...
doi:10.3127/ajis.v6i2.310
fatcat:57zzkqzw2bdgndhjp5tumgicd4
Research Challenges for Data Mining in Science and Engineering
[chapter]
2008
Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
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for new, data-intensive methods to conduct research in science and engineering. ...
, and understanding of patterns and knowledge, (3) stream data mining, (4) mining moving object data, RFID data, and data from sensor networks, (5) spatiotemporal and multimedia data mining, (6) mining ...
data mining: Data mining by integration of sophisticated scientific and engineering domain knowledge Besides general data mining methods and tools for science and engineering, each scientific or engineering ...
doi:10.1201/9781420085877.pt1
fatcat:ljs2uybdofgkxfpouawfekdaz4
Aspects of knowledge discovery in technical data
2002
Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV
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Keywords: knowledge discovery in scientific data, data mining, dimensional analysis THE KNOWLEDGE DISCOVERY PROCESS FOR SCIENTIFIC DATA Based on the standard knowledge discovery (data mining) process 4 ...
This paper emphasizes the need for a modified knowledge discovery process for engineering (and other scientific domains) and shows the differences to the traditional knowledge discovery in data bases. ...
In the following chapters these knowledge discovery steps and the implications for the use with scientific data are discussed in more detail. ...
doi:10.1117/12.460218
dblp:conf/dmkdttt/BrucknerR02
fatcat:x3zyvhnf7fa6bm3gce2dl2du6e
Concept Formation in Scientific Knowledge Discovery from a Constructivist View
[chapter]
2009
Scientific Data Mining and Knowledge Discovery
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This chapter argues that the computer-aided scientific knowledge discovery tool should facilitate scientific knowledge development through assisting scientists to build first-person knowledge and thirdperson ...
A number of challenges for designing such a system have been discussed. ...
in model construction in the scientific knowledge discovery and Knowledge Discovery in Databases (KDD) area [56] , [57] . ...
doi:10.1007/978-3-642-02788-8_5
fatcat:fmm2sepq4vg2hkagvbmusrtiam
A Novel Model for Global Customer Retention Using Data Mining Technology
[chapter]
2009
Data Mining and Knowledge Discovery in Real Life Applications
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This chapter deals with how to use data mining technology to find interesting pattern, which can be organized for global customer retention. ...
Customer data and information technology (IT) tools shape into the foundation upon which any successful CRM strategy is built. ...
Data Mining and Knowledge Discovery in Real Life Applications 252 usage behavior. ...
doi:10.5772/6453
fatcat:5g5ix2bk7bh7je7zhxaegw7tgi
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 ...
In view of the above facts, the paper gives an introduction to the synergistic challenges in "data-intensive" science and "exascale" computing for resolving "big data analytics" and "data science" issues ...
INTRODUCTION "Data mining" for "knowledge discovery in databases" and associated computational operations first introduced in the mid-1990 s can no longer be used to analyse the so-called "big data". ...
doi:10.3844/jcssp.2014.2658.2665
fatcat:whtc2on6vncq5hayilctdfpvgu
Redescription Mining and Applications in Bioinformatics
[chapter]
2009
Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
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We present algorithms for redescription mining based on formal concept analysis and applications of redescription mining to multiple biological datasets. ...
., genes, proteins) and a collection of descriptors defined over this set, the goal of redescription mining is to use the given descriptors as a vocabulary and find subsets of data that afford multiple ...
Acknowledgements This work was supported in part by NSF grants CNS-0615181, ITR-0428344, EMT-0829835, and CNS-0103708, and NIH Grant 1R01EB0080161-01A1. ...
doi:10.1201/9781420086850.ch22
fatcat:lelc5qyxrzggnkuahgu7ticihe
Big data, big results: Knowledge discovery in output from large-scale analytics
2014
Statistical analysis and data mining
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We focus on the value of knowledge discovery methods and the challenges in extracting clinically relevant knowledge from big results. ...
We believe our analyses are both scientifically and methodologically valuable as they reveal information about how methods/algorithms perform under various circumstances, as well as provide a basis for ...
Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation. ...
doi:10.1002/sam.11237
fatcat:rflvfocj7ne5pfbb7conzv6gqq
Rough Set Theory — Fundamental Concepts, Principals, Data Extraction, and Applications
[chapter]
2009
Data Mining and Knowledge Discovery in Real Life Applications
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Rough Set is the knowledge discovery or Data Mining in database. ...
Knowledge Discovery in Database -KDD Knowledge Discovery in Database -KDD is a process, with several stages, no trivial, interactive and iterative, for the identification of comprehensible patterns, valid ...
Table 9 Conclusion of analysis: In this analysis, no data was excluded. c. Given analysis of condition attributes in Table 9 , it can be observed that the same data exists in proceeding tables. ...
doi:10.5772/6440
fatcat:wn2dgx5u3rdk5egnzzmq7ko4my
Simultaneous optimization of complex mining tasks with a knowledgeable cache
2005
Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05
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With an increasing use of data mining tools and techniques, we envision that a Knowledge Discovery and Data Mining System (KDDMS) will have to support and optimize for the following scenarios: 1) Sequence ...
This paper presents a systematic mechanism to optimize for the above cases, targetting the class of mining queries involving frequent pattern mining on one or multiple datasets. ...
With an increasing use of data mining tools and techniques, we envision that a Knowledge Discovery and Data Mining System (KDDMS) will have to support and optimize for the following scenarios: ¢ Sequence ...
doi:10.1145/1081870.1081943
dblp:conf/kdd/JinSA05
fatcat:ktnurrcayjbqfbp7g3g2paxrbq
Method evaluation, parameterization, and result validation in unsupervised data mining: A critical survey
2019
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
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In more general terms, we call for the development of a true "Data Science" that -based on work in other domains, results in ML, and existing tools -develops needed data generators and builds up the knowledge ...
values, and 3) work comparing mining results with the ground truth in the data. ...
Acknowledgments We are grateful to Matthijs van Leeuwen, Arno Siebes, and Jilles Vreeken for reviewing preliminary versions of this article, Marc Plantevit, Wouter Duivesteijn, and Arnaud Soulet for providing ...
doi:10.1002/widm.1330
fatcat:f7dvoxeebfbt3dw4ft6kimbi6u
A data mining framework for optimal product selection in retail supermarket data
2000
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '00
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In recent years, data mining researchers have developed efficient association rule algorithms for retail market basket analysis. ...
Therefore, in this paper, the authors present an important generalization of the existing model in order to make it suitable for supermarket data as well, and to enable retailers to add category restrictions ...
Association rule mining [2] can help retailers to efficiently extract this knowledge from large retail databases. We assume some familiarity with the basic notions of association rule mining. ...
doi:10.1145/347090.347156
dblp:conf/kdd/BrijsGSVW00
fatcat:65eu6ltv5zf3bif25qdiumzbpq
Elastic stream processing in the Cloud
2013
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
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In contrast to traditional databases, stream processing systems perform continuous queries and handle data on-the-fly. ...
Stream processing is a computing paradigm that has emerged from the necessity of handling high volumes of data in real time. ...
These data streams include relevant information that can be revealed by data mining and processing. ...
doi:10.1002/widm.1100
fatcat:o67z4wzq75cbboef2ex5a7lmma
Privacy-preserving data integration and sharing
2004
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery - DMKD '04
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Integrating data from multiple sources has been a longstanding challenge in the database community. ...
Techniques such as privacy-preserving data mining promises privacy, but assume data has integration has been accomplished. ...
Privacy-preserving integration and sharing of research data in health sciences has become crucial to enabling scientific discovery. ...
doi:10.1145/1008694.1008698
dblp:conf/dmkd/CliftonKDSVES04
fatcat:5zotyfq2ercnrkonhc2hh5rgd4
Research on spatial data mining based on uncertainty in Government GIS
2010
2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery
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Uncertainty is the intrinsic property of spatial data and one of important factors affecting the course of spatial data mining. ...
There are diversiform forms for the essentiality and aspect of uncertainty in the spatial objects of geographic information system. ...
And all the spatial data used in this paper comes from the database in Government GIS. ...
doi:10.1109/fskd.2010.5569275
dblp:conf/fskd/LiSL10
fatcat:szpcsbnfbrfnzniogn4syy4yde
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