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PSO based Multidimensional Data Clustering: A Survey
2014
International Journal of Computer Applications
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Data clustering is considered as one of the most promising data analysis methods in data mining and on the other side K-Means is the well known partitional clustering technique. ...
They have used PSO and K-Means algorithm in sequence for data clustering. ...
Data clustering is an interesting issue in data mining and number of PSO based techniques are proposed in the state-of-the-art. ...
doi:10.5120/15296-4040
fatcat:2p6c57awv5fp3ome2hy6yocut4
An OD Flow Clustering Method Based on Vector Constraints: A Case Study for Beijing Taxi Origin-Destination Data
2020
ISPRS International Journal of Geo-Information
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mode, divergence mode, and convergence mode) with representative travel trends are found. ...
of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. ...
It can expand multidimensional data analysis by step clustering. ...
doi:10.3390/ijgi9020128
fatcat:jhoo32ndxzewtnfo6dc3lt54om
Image Information Mining System Evaluation Using Information-Theoretic Measures
2005
EURASIP Journal on Advances in Signal Processing
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for successful content-based image retrieval and image information mining. ...
Image data information systems require both database and visual capabilities, but there is a gap between these systems. ...
Convergence of learning process How efficient is the mining system learning convergence? ...
doi:10.1155/asp.2005.2153
fatcat:lrtuvxsh2zgddi3nzpyy3wnzdy
Multidimensional Scaling by Deterministic Annealing with Iterative Majorization Algorithm
2010
2010 IEEE Sixth International Conference on e-Science
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Multidimensional scaling (MDS) is a general term for the techniques of configuration of high dimensional data into target dimensional space in terms of pairwise proximity information, while distance between ...
It turns out that applying deterministic annealing to multidimensional scaling problem improves the mapping quality due to avoiding local optima and shows high reliability in our experimental results. ...
INTRODUCTION The recent explosion of publicly available biology gene sequences, chemical compounds, and various scientific data offers an unprecedented opportunity for data mining. ...
doi:10.1109/escience.2010.45
dblp:conf/eScience/BaeQF10
fatcat:5vc5vzs4gbbmzpsnfweqe6oqyi
An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer
2019
Complexity
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filter, and multiple fading factor and forgetting factor for east and north velocity measurement are designed in the algorithm, respectively, which can effectively weaken the coupling relationship between ...
The strap-down inertial navigation system (SINS) is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine. ...
However, the complexity of working environment in coal mines has brought great difficulties for the mining of coal mine and the safety problems of coal mines have received growing considerable attention ...
doi:10.1155/2019/3172501
fatcat:beup663t4jhefhkmqbmrtnd5ii
A Robust and Scalable Solution for Interpolative Multidimensional Scaling with Weighting
2013
2013 IEEE 9th International Conference on e-Science
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Advances in modern bio-sequencing techniques have led to a proliferation of raw genomic data that enables an unprecedented opportunity for data mining. ...
Among the known algorithms, we use Multidimensional Scaling (MDS) to reduce the dimension of original data and Pairwise Clustering, and to classify the data. ...
Our thanks to Mina Rho and Haixu Tang from Center for Genomics and Bioinformatics for providing the DNA and RNA data, and Larissa Stanberry from Seattle Children's Research Institute for providing the ...
doi:10.1109/escience.2013.30
dblp:conf/eScience/RuanF13
fatcat:des7ike4sza3pnsdklec2pcrju
MultiClust special issue on discovering, summarizing and using multiple clusterings
2014
Machine Learning
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In such data, one typically observes several valid groupings, i.e. each data object fits in different roles. ...
Traditionally, clustering has focused on discovering a single grouping of the data. In many applications, however, data is collected for multiple analysis tasks. ...
in clustering and pattern mining. ...
doi:10.1007/s10994-014-5445-0
fatcat:mahkn62jb5hvjecq4wh4fun7xe
Phylogenomic Resolution of the Phylogeny of Laurasiatherian Mammals: Exploring Phylogenetic Signals within Coding and Noncoding Sequences
2017
Genome Biology and Evolution
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Previous studies mainly relied on coding sequences (CDS) and seldom used noncoding sequences. ...
Here, by data mining public genome data, we compiled an intron data set of 3,638 genes (all introns from a protein-coding gene are considered as a gene) (19,055,073 bp) and a CDS data set of 10,259 genes ...
Acknowledgments We thank all members of Zhang's lab and Dr Xing-Xing Shen for helpful discussion. ...
doi:10.1093/gbe/evx147
pmid:28830116
pmcid:PMC5737624
fatcat:fiorpipkgna2le6fbbzqobn54m
Book review: A review of chaos, catastrophe, and human affairs: Applications of nonlinear dynamics to work, organizations, and social evolution by Stephen J. Guastello
1998
Discrete Dynamics in Nature and Society
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point where you mention the derivation of the polynomial regression equations for the catastrophe model, please add, that the chapter also includes statistical models for capturing the Lyapunov exponent and ...
Your coverage of traditional viewpoints in creativity, i.e., Guilford's divergent and convergent cognition are especially relevant as those are exactly the ingredients of a chaotic attractor, which metaphorically ...
Some authors like to emphasize that there is not just one Lyapunov exponent, but a spectrum for each attractor; chaos is the result of convergent and divergent forces, so taking ranges and ratios of and ...
doi:10.1155/s1026022698000119
fatcat:qdmg54r3dfggnlpp7vl4xkdf6q
Editorial
2015
Intelligent Data Analysis
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in terms of accuracy and convergence speed. ...
This results in improvements in the execution time for reconstructing the tree when old or new customer sequences are added into the original database to be reduced by using pre-large sequences. ...
doi:10.3233/ida-150752
fatcat:tkvpscenoren3mlybamx42huki
Page 36 of Psychological Abstracts Vol. 88, Issue 1
[page]
2001
Psychological Abstracts
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
—Examined the relationship between certain psychological factors (i.e. field dependence/field independence, convergence/ divergence and working memory capacity) and the effect of these factors on the performance ...
In terms of word association test (WAT) responses, only the convergence/di- vergence dimension of cognitive styles showed a significant relationship with the WAT.
295. ...
Unsupervised Two-Way Clustering of Metagenomic Sequences
2012
Journal of Biomedicine and Biotechnology
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Further, we handle the high-dimensionality and sparsity associated with the data, by grouping the set of words comprising the reads, resulting in a two-way mixture model. ...
In this paper, we formulate an unsupervised naive Bayes multispecies, multidimensional mixture model for reads from a metagenome. ...
Acknowledgment The authors wish to thank Jia Li for her useful insights into the two-way Poisson mixture model problem and the reviewers for their valuable comments and suggestions. ...
doi:10.1155/2012/153647
pmid:22577288
pmcid:PMC3336163
fatcat:hv7gezxyunau5c5dmhdervzdky
Pattern recognition algorithms based on space-filling curves and orthogonal expansions
2001
IEEE Transactions on Information Theory
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The classical problem of constructing a multidimensional pattern classifier in the Bayesian framework is considered. ...
The learning sequence transformed into the unit interval is used to estimate the coefficients in an orthogonal expansion of the Bayes decision rule. ...
ACKNOWLEDGMENT The author wishes to thank the referees for their many stimulating comments and suggestions, which led to some generalizations of the earlier results and improved the presentation of the ...
doi:10.1109/18.930927
fatcat:tdaph67r5jd5db775c6gxkbxwq
Functionally diverging molecular quasi-species evolve by crossing two enzymes
2006
Proceedings of the National Academy of Sciences of the United States of America
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This approach to evolutionary data mining serves to identify emerging molecular quasi-species and indicates potential trajectories available for further protein evolution. directed evolution ͉ DNA shuffling ...
We have generated enzyme variants by stochastic recombinations of DNA encoding two homologous detoxication enzymes, human glutathione transferases M1-1 and M2-2, and explored their catalytic versatilities ...
Human GST M1-1 and GST M2-2 are homologous proteins with a recent divergence, presumably involving gene convergence or exon shuffling (9) . ...
doi:10.1073/pnas.0604030103
pmid:16829572
pmcid:PMC1544140
fatcat:4j65hq63tnbu5hgaq42zyutm3m
Adaptive Privacy-Preserving Visualization Using Parallel Coordinates
2011
IEEE Transactions on Visualization and Computer Graphics
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Researchers in the field of data mining have proposed different techniques over the years for privacy-preserving data publishing and subsequent mining techniques on such sanitized data. ...
Corporate data, medical records, etc. are rich in analytical value but cannot be shared without first going through a transformation step where explicit identifiers are removed and the data is sanitized ...
Compute degree of convergence and divergence for both axes. 4. Convergence and divergence are mirrors of each other. ...
doi:10.1109/tvcg.2011.163
pmid:22034343
fatcat:4cijpozjoneqhhopjswobox3oa
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