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Graphical Representation and Exploratory Visualization for Decision Trees in the KDD Process
2012
2012 IEEE Ninth Electronics, Robotics and Automotive Mechanics Conference
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This article presents a proposal of representation and scheme of exploratory visualization for Decision Trees in the KDD (Knowledge Discovery in Database) process, specifically in the data mining stage ...
In this sense, this work pursues to introduce new schemes of visualizations that allow specifically understand how the data mining models work internally. ...
Criteria for Evaluating Treemap Visualizations It was noted that the treemap technique allows information to visually represent hierarchical structures in 2D, and is capable of representing large collections ...
doi:10.1109/cerma.2012.40
fatcat:mqhppnigdrd6bevzayocsbwce4
Graphical representation and exploratory visualization for Decision Trees in the KDD process
2012
2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI)
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This article presents a proposal of representation and scheme of exploratory visualization for Decision Trees in the KDD (Knowledge Discovery in Database) process, specifically in the data mining stage ...
In this sense, this work pursues to introduce new schemes of visualizations that allow specifically understand how the data mining models work internally. ...
Criteria for Evaluating Treemap Visualizations It was noted that the treemap technique allows information to visually represent hierarchical structures in 2D, and is capable of representing large collections ...
doi:10.1109/clei.2012.6427162
dblp:conf/clei/RojasV12
fatcat:6n5gfanvdfauzpu52atnhkufme
Graphical Representation and Exploratory Visualization for Decision Trees in the KDD Process
2013
Procedia - Social and Behavioral Sciences
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This article presents a proposal of representation and scheme of exploratory visualization for Decision Trees in the KDD (Knowledge Discovery in Database) process, specifically in the data mining stage ...
In this sense, this work pursues to introduce new schemes of visualizations that allow specifically understand how the data mining models work internally. ...
Criteria for Evaluating Treemap Visualizations It was noted that the treemap technique allows information to visually represent hierarchical structures in 2D, and is capable of representing large collections ...
doi:10.1016/j.sbspro.2013.02.033
fatcat:sinxkhxxbjfmlmr2qbxegwirla
Visualizing big network traffic data using frequent pattern mining and hypergraphs
2013
Computing
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Communication logs, however, can be massive, which necessitates designing effective visualization techniques for large data sets. ...
Previous research has explored using parallel-coordinate plots for visualizing network traffic flows. However, such plots do not scale to data sets with thousands of even millions of flows. ...
Scaling to large data sets In this section, we show how our scheme complements existing commonly-used approaches, which visualize every individual connection, but can only scale to small data sets, by ...
doi:10.1007/s00607-013-0282-8
fatcat:rf6hb5owpvb57eooecdfd2lhne
Knowledge Map: Toward a New Approach Supporting the Knowledge Management in Distributed Data Mining
[article]
2019
arXiv
pre-print
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Other Versions
2007
Third International Conference on Autonomic and Autonomous Systems (ICAS'07)
unpublished
doi:10.1109/conielecomp.2007.80 fatcat:lhgns7pevzfdjgbn6f6izmiwja
doi:10.1109/conielecomp.2007.80 fatcat:lhgns7pevzfdjgbn6f6izmiwja
This new approach aims to manage efficiently mined knowledge in large scale distributed platform such as Grid. ...
This causes problems of not only knowledge management but also visualization in data mining. ...
We aim also offer an effective knowledge map to facilitate the visualization for data mining. ...
arXiv:1910.10547v1
fatcat:yiukwrzpxjd4bimqjawsqp5lfu
A Review on Clustering Technique
2015
International Journal on Recent and Innovation Trends in Computing and Communication
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Hidden Knowledge is very important in data mining field. ...
Large data set have many hidden pattern which have very crucial information, Clustering is such technique which find the hidden pattern from the large data. ...
Data mining derives its name from the similarities between searching for valuable information in a large database. ...
doi:10.17762/ijritcc2321-8169.1503136
fatcat:rdt7mpmyvnbm3ph6o7v72wmpdy
Evaluating knowledge transfer and zero-shot learning in a large-scale setting
2011
CVPR 2011
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To this end, we provide an extensive evaluation of three popular approaches to KT on a recently proposed large-scale data set, the ImageNet Large Scale Visual Recognition Competition 2010 data set. ...
We also propose and describe several extensions of the evaluated approaches that are necessary for this large-scale study. ...
We evaluate knowledge transfer on the recently proposed ImageNet data set [7] , specifically, on the associated ImageNet Large Scale Visual Recognition Competition 2010 (ILSVRC10) subset [2] . ...
doi:10.1109/cvpr.2011.5995627
dblp:conf/cvpr/RohrbachSS11
fatcat:uc655tnp7bb6jau4bcvdudjgzy
From visual data exploration to visual data mining: A survey
2003
IEEE Transactions on Visualization and Computer Graphics
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We survey work on the different uses of graphical mapping and interaction techniques for visual data mining of large data sets represented as table data. ...
Basic terminology related to data mining, data sets, and visualization is introduced. ...
Visual Data Exploration for Mining Mining tasks usually demand techniques capable of handling large amounts of multidimensional data, often in the format of Data Tables or relational databases. ...
doi:10.1109/tvcg.2003.1207445
fatcat:g6lrnvirmfdy7k55c6w65p3fpi
Partial Ordered Structure Radial Tree: A New Method for Big Data Visualization
2016
ICIC Express Letters
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The raise of partial ordered structure radial tree provides a useful way for knowledge visualization, and it is of great significance to knowledge discovery and data mining of big data. ...
Partial ordered structure diagram has been widely applied to knowledge discovery, data mining and many other domains due to its better visualization effect. ...
The authors also gratefully acknowledge the reviewers for their valuable comments and suggestions to the paper. ...
doi:10.24507/icicel.10.05.1181
fatcat:zzqjdhkmnvfvvd6gm2tq3lu7ha
Image information mining : exploration of Earth observation archives
2003
Geographica Helvetica
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It has been known for many years that classical image file text annotation is prohibitive for large data bases. ...
In order to implement the hierarchical representation of the image information content, the data is pre-processed. First, the image features are extracted for different image scales. ...
doi:10.5194/gh-58-154-2003
fatcat:hvgfd2p33zettm2u2q3uj4jui4
Visualizing Attribute Interdependencies Using Mutual Information, Hierarchical Clustering, Multidimensional Scaling, and Self-organizing Maps
2007
2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)
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We further visualize the attribute interdependencies using a host of techniques, including hierarchical clustering, multidimensional scaling, and self-organizing maps. ...
Data pre-processing tends to be the most critical and time-consuming step during data mining processes. ...
For example, if two attributes contain largely the same information, it is possible to eliminate one, thereby reducing the data mining effort as well as making the data set more compact. ...
doi:10.1109/hicss.2007.608
dblp:conf/hicss/NazarethSZ07
fatcat:ngevwjt24vanrka7xwjfefxblq
Novel Data Structure Modeling Model based on Hierarchical Data Analysis and Parsing
2017
DEStech Transactions on Social Science Education and Human Science
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In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. ...
In addition to structural modeling for this site text data, also we discuss some of the three-dimensional Markov model energy minimization of machine learning algorithms. ...
Theme is a model for the analysis of large-scale text hierarchical Bayesian model, which uses a fast unsupervised machine learning algorithms to extract the low-dimensional mathematical representation, ...
doi:10.12783/dtssehs/icsste2017/9417
fatcat:mi53ux4ryzdr7pjb7b2enb7ifi
VisANT: an integrative framework for networks in systems biology
2008
Briefings in Bioinformatics
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Among the tools being developed to meet this challenge is VisANT (freely available at http://visant.bu.edu) which integrates, mines and displays hierarchical information. ...
Challenges to integrating modeling (discrete or continuous) and simulation capabilities into such visual mining software are briefly discussed. University. ...
Acknowledgements We thank colleagues, students and other users of VisANT for their valuable comments and suggestions in improving all facets of the system. ...
doi:10.1093/bib/bbn020
pmid:18463131
pmcid:PMC2743399
fatcat:7ollymkv3zcodgtlxpjvp23b2y
Analysis Of Diverse Clustering Tools In Data Mining
2014
Zenodo
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These challenges pave the way for the emergence of powerful expansive data mining clustering softwares. ...
Clustering in data mining is an unsupervised learning technique of aggregating the data objects into meaningful groups such that the intra cluster similarity of objects are maximized and inter cluster ...
PermutMatrix PermutMatrix is a data mining tool [4]-[9] specifically used for analysing and visualizing gene data. ...
doi:10.5281/zenodo.1336475
fatcat:r55g3ue75jbdnpp2zkocsilbwm
Tenth international workshop on multimedia data mining
2011
SIGKDD Explorations
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In this report we provide a summary of the tenth Multimedia Data Mining Workshop that was held in conjunction with the 16th ACM ...
The fifth paper "Large Scale Image Clustering with Support Vector Machine based on Visual Keywords" (Chang, Ip, Feng) continues the popular at the Workshop topic of image mining using visual keywords ...
-Data mining of large datasets of user generated content (e.g., YouTube, Flickr, etc.). ...
doi:10.1145/1964897.1964909
fatcat:pmhjo25aorhslicey2ljgsyo3q
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