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ONLINE VENDOR NEUTRAL INTRO TO DATA MINING FOR ABSOLUTE BEGINNERS
(no charge)
A non-technical data mining introduction for beginners
January 29, 2008, 10AM-11AM PST
February 19, 2008, 4PM-5PM PST
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nature of the predictive mechanism
**Evaluation criteria: how predictive models can be assessed and
their value measured
**Specific background knowledge to prepare you to begin a data
mining project.
To register: http://salford.webex.com
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lisas@...
ONLINE VENDOR NEUTRAL INTRO TO DATA MINING FOR ABSOLUTE BEGINNERS
(no charge)
A non-technical data mining introduction for beginners
January 29, 2008, 10AM-11AM PST
February 19, 2008, 4PM-5PM PST
To register: http://salford.webex.com
This one-hour webinar is a perfect place to start if you are new to
data mining and have little-to-no background in statistics or
machine learning.
In one hour, we will discuss:
**Data basics: what kind of data is required for data mining and
predictive analytics; In what format must the data be; what steps
are necessary to prepare data appropriately
**What kinds of questions can we answer with data mining
**How data mining models work: the inputs, the outputs, and the
nature of the predictive mechanism
**Evaluation criteria: how predictive models can be assessed and
their value measured
**Specific background knowledge to prepare you to begin a data
mining project.
To register: http://salford.webex.com
Contact me if the January 29th or February 19th dates/times are
inconvenient and you wish to be put on our webinar notification list.
Sincerely,
Lisa Solomon
lisas@...
Editorial
A special issue on applications of ensemble methods Page 1
Belur V. Dasarathy
Applications of ensemble methods Pages 2-3
Nikunj C. Oza and Kagan Tumer
Regular papers
Classifier ensembles: Select real-world applications Pages 4-20
Nikunj C. Oza and Kagan Tumer
Methods for person identification on a pressure-sensitive floor:
Experiments with multiple classifiers and reject option Pages 21-40
Jaakko Suutala and Juha Röning
A new boosting algorithm for improved time-series forecasting with
recurrent neural networks Pages 41-55
Mohammad Assaad, Romuald Boné and Hubert Cardot
Dynamic integration of classifiers for handling concept drift Pages 56-68
Alexey Tsymbal, Mykola Pechenizkiy, Pádraig Cunningham and Seppo Puuronen
Intrusion detection in computer networks by a modular ensemble of
one-class classifiers Pages 69-82
Giorgio Giacinto, Roberto Perdisci, Mauro Del Rio and Fabio Roli
An ensemble based data fusion approach for early diagnosis of
Alzheimer's disease Pages 83-95
Robi Polikar, Apostolos Topalis, Devi Parikh, Deborah Green, Jennifer
Frymiare, John Kounios and Christopher M. Clark
Ensemble methods for anomaly detection and distributed intrusion
detection in Mobile Ad-Hoc Networks Pages 96-119
João B.D. Cabrera, Carlos Gutiérrez and Raman K. Mehra
Using classifier ensembles to label spatially disjoint data Pages 120-133
Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer
and W. Philip Kegelmeyer
Finding FUN in FUsioN
Finding FUN in FUsioN - XXX Page 134
Reviewers (2006) – A note of appreciation Pages 135-137
Articles in Press - available online Pages 138-139
Information Fusion
Volume 8, Issue 4, Pages 335-416 (October 2007)
Editorial
Information Fusion - A status update
Pages 335-336
Belur V. Dasarathy
Regular papers
Robust memory-efficient data level information fusion of multi-modal
biometric images
Pages 337-346
Afzel Noore, Richa Singh and Mayank Vatsa
Robust image registration for fusion
Pages 347-353
Markus Müller, Wolfgang Krüger and Günter Saur
Genetic perceptual shaping: Utilizing cover image and conceivable
attack information during watermark embedding
Pages 354-365
Asifullah Khan and Anwar M. Mirza
An optimized architecture for classification combining data fusion and
data-mining
Pages 366-378
George Gigli, Éloi Bossé and George A. Lampropoulos
Engine fault diagnosis based on multi-sensor information fusion using
Dempster¡VShafer evidence theory
Pages 379-386
Otman Basir and Xiaohong Yuan
Analyzing the combination of conflicting belief functions
Pages 387-412
Philippe Smets
------------------------------
Finding FUN in FUsioN
Finding FUN in FUsioN ¡V XXIX
Page 413
Articles in Press - available online
Pages 414-415
Due to increasing number of submissions, the Journal is seeking
qualified and experienced reviewers in the areas of interest covered
by the Information Fusion Journal. We currently need significant
number of new reviewers to meet the demand. We would also like to hear
from qualified reviewers with experience in managing reviews, who
would like to occasionally manage the review process on behalf of the
editor.
If you are (or any of your colleagues is) interested in helping
out,either as reviewers (or additionally as review process managers),
please reply to belurd@... with a short biography (emphasizing
your work in Information Fusion area) and a link to your home page, if
any. Pleas also include a list of topics wherein you feel qualified
and comfortable for helping us with reviews so that we can identify the
manuscripts appropriate for your review.
Thanks
B.V.Dasarathy
Editor-in-Chief, Information Fusion
Information Fusion
Volume 8, Issue 3, Pages 223-334 (July 2007)
Special Issue on Concurrent Learning and Fusion
Edited by Leonid Perlovsky
Editorial
A special issue on concurrent learning and fusion
Page 223
Belur V. Dasarathy
Guest Editorial
Concurrent learning and fusion
Pages 224-226
Leonid Perlovsky
Regular papers
A new approach to higher-level information fusion using associative
learning in semantic networks of spiking neurons
Pages 227-251
Neil A. Bomberger, Allen M. Waxman, Bradley J. Rhodes and Nathan A.
Sheldon
Robust automatic target recognition using learning classifier systems
Pages 252-265
B. Ravichandran, Avinash Gandhe, Robert Smith and Raman Mehra
Hierarchical Collective Agent Network (HCAN) for efficient fusion and
management of multiple networked sensors
Pages 266-280
Qiuming Zhu, Stuart L. Aldridge and Tomas N. Resha
Temporal uncertainty reasoning networks for evidence fusion with
applications to object detection and tracking
Pages 281-294
Chilukuri K. Mohan, Kishan G. Mehrotra, Pramod K. Varshney and Jie Yang
Taxonomic knowledge structure discovery from imagery-based data using
the neural associative incremental learning (NAIL) algorithm
Pages 295-315
Bradley J. Rhodes
Concurrent multi-target localization, data association, and navigation
for a swarm of flying sensors
Pages 316-330
Ross W. Deming and Leonid I. Perlovsky
Finding FUN in FUsioN
Finding FUN in FUsioN - XXVIII
Page 331
New Books Announcement – January 2007
Page 332
Articles in Press - available online
Pages 333-334
Information Fusion
Volume 7, Issue 3, Page 247-340 (September 2006)
Editorial
Our silver jubilee issue—Arriving at another milestone
Pages 247-249
Belur V. Dasarathy Dr.
Regular papers
On multisensor image fusion performance limits from an estimation
theory perspective
Pages 250-263
Rick S. Blum
Moderate diversity for better cluster ensembles
Pages 264-275
Stefan T. Hadjitodorov, Ludmila I. Kuncheva and Ludmila P. Todorova
The TBM global distance measure for the association of uncertain
combat ID declarations
Pages 276-284
Branko Ristic and Philippe Smets
Target motion analysis and track association with a network of
proximity sensors
Pages 285-303
Régis Donati and Jean-Pierre Le Cadre
Multi-sensor fusion: an Evolutionary algorithm approach
Pages 304-330
Igor V. Maslov and Izidor Gertner
Incomplete linguistic preference relations and their fusion
Pages 331-337
Zeshui Xu
Finding FUN in FUsioN
Finding FUN in FUsioN—XXIV
Page 338
Articles in Press - available online
Pages 339-340
http://www.isder.ceser.res.in/ijts/cont/ijts-s06-cont.html
B.V. Dasarathy
Editor
Editor-in-Chief:
R. K. S. Rathore,
Professor, Department of Mathematics, Indian Institute of Technology,
Kanpur-208016, INDIA,
email: ijts@...
Executive Editor:
Tanuja Srivastava,
Department of Mathematics, Indian Institute of Technology,
Roorkee-247667, INDIA.
email: tanujfma@...
Identity fusion in unsupervised environments • EDITORIAL
Pages 157-160
Belur V. Dasarathy
Regular papers
Exploitation of a priori knowledge for information fusion
Pages 161-175
Éloi Bossé, Pierre Valin, Anne-Claire Boury-Brisset and Dominic Grenier
Fusionplex: resolution of data inconsistencies in the integration of
heterogeneous information sources
Pages 176-196
Amihai Motro and Philipp Anokhin
Comparative implementation of two fusion schemes for multiple
complementary FLIR imagery classifiers
Pages 197-206
Pierre Valin, Francois Rhéaume, Claude Tremblay, Dominic Grenier,
Anne-Laure Jousselme and Éloi Bossé
Information fusion approaches to the automatic pronunciation of print
by analogy
Pages 207-220
R.I. Damper and Y. Marchand
GPS/IMU data fusion using multisensor Kalman filtering: introduction
of contextual aspects
Pages 221-230
Francois Caron, Emmanuel Duflos, Denis Pomorski and Philippe Vanheeghe
Induced uncertain linguistic OWA operators applied to group decision
making
Pages 231-238
Zeshui Xu
--------------
Finding FUN in FUsioN-XXIII
Page 239
In memoriam: Philippe Smets (1938–2005)
Pages 240-244
Articles in Press - available online
Pages 245-246
TOP25 Hottest Articles - downloaded during October, November and
December, 2005 - within the journal Information Fusion
1. Urban remote sensing using multiple data sets: Past, present,
and future • Article
Information Fusion, Volume 6, Issue 4, 1 December 2005, Pages
319-326
Gamba, P.; Dell\'Acqua, F.; Dasarathy, B.V.
2. An integrated system for automatic road mapping from
high-resolution multi-spectral satellite imagery by information fusion
• Article
Information Fusion, Volume 6, Issue 4, 1 December 2005, Pages
257-273
Jin, X.; Davis, C.H.
3. Integration of 3D data in SAR mission planning and image
interpretation in urban areas • Article
Information Fusion, Volume 6, Issue 4, 1 December 2005, Pages
301-310
Soergel, U.; Schulz, K.; Thoennessen, U.; Stilla, U.
4. A framework for GIS and imagery data fusion in support of
cartographic updating • Article
Information Fusion, Volume 6, Issue 4, 1 December 2005, Pages
311-317
Weis, M.; Muller, S.; Liedtke, C.-E.; Pahl, M.
5. Using the Dempster-Shafer method for the fusion of LIDAR data
and multi-spectral images for building detection • Article
Information Fusion, Volume 6, Issue 4, 1 December 2005, Pages
283-300
Rottensteiner, F.; Trinder, J.; Clode, S.; Kubik, K.
6. Image fusion techniques for remote sensing applications • Article
Information Fusion, Volume 3, Issue 1, 1 March 2002, Pages 3-15
Simone, G.; Farina, A.; Morabito, F.C.; Serpico, S.B.; Bruzzone, L.
7. Multi-sensor fusion: an Evolutionary algorithm approach • Article
Information Fusion
Maslov, I.V.; Gertner, I.
8. Engine fault diagnosis based on multi-sensor information fusion
using Dempster-Shafer evidence theory • Article
Information Fusion
Basir, O.; Yuan, X.
9. Multi-sensor management for information fusion: issues and
approaches • Article
Information Fusion, Volume 3, Issue 2, 1 June 2002, Pages 163-186
Xiong, N.; Svensson, P.
10. An IHS and wavelet integrated approach to improve pan-sharpening
visual quality of natural colour IKONOS and QuickBird images • Article
Information Fusion, Volume 6, Issue 3, 1 September 2005, Pages
225-234
Zhang, Y.; Hong, G.
11. Pixel-based and region-based image fusion schemes using ICA
bases • Article
Information Fusion
Mitianoudis, N.; Stathaki, T.
12. Fusion of 3D building models derived from first and last pulse
laserscanning data • Article
Information Fusion, Volume 6, Issue 4, 1 December 2005, Pages
275-281
Vogtle, T.; Steinle, E.
13. Interband structure modeling for Pan-sharpening of very
high-resolution multispectral images • Article
Information Fusion, Volume 6, Issue 3, 1 September 2005, Pages
213-224
Garzelli, A.; Nencini, F.
14. GPS/IMU data fusion using multisensor Kalman filtering:
introduction of contextual aspects • Article
Information Fusion
Caron, F.; Duflos, E.; Pomorski, D.; Vanheeghe, P.
15. Robust image fusion using a statistical signal processing
approach • Article
Information Fusion, Volume 6, Issue 2, 1 June 2005, Pages 119-128
Blum, R.S.
16. Comparison of RADARSAT-1 and IKONOS satellite images for urban
features detection • Article
Information Fusion, Volume 6, Issue 3, 1 September 2005, Pages
243-249
Weydahl, D.J.; Bretar, F.; Bjerke, P.
17. Real-time data mining of non-stationary data streams from sensor
networks • Article
Information Fusion
Cohen, L.; Avrahami-Bakish, G.; Last, M.; Kandel, A.; Kipersztok, O.
18. A cluster ensemble method for clustering categorical data • Article
Information Fusion, Volume 6, Issue 2, 1 June 2005, Pages 143-151
He, Z.; Xu, X.; Deng, S.
19. Diversity creation methods: a survey and categorisation • Article
Information Fusion, Volume 6, Issue 1, 1 March 2005, Pages 5-20
Brown, G.; Wyatt, J.; Harris, R.; Yao, X.
20. Robust memory-efficient data level information fusion of
multi-modal biometric images • Article
Information Fusion
Noore, A.; Singh, R.; Vatsa, M.
21. Diversity measures for multiple classifier system analysis and
design • Article
Information Fusion, Volume 6, Issue 1, 1 March 2005, Pages 21-36
Windeatt, T.
22. Logic-based approaches to information fusion • Article
Information Fusion
Gregoire, E.; Konieczny, S.
23. Classifier selection for majority voting • Article
Information Fusion, Volume 6, Issue 1, 1 March 2005, Pages 63-81
Ruta, D.; Gabrys, B.
24. Pixel- and region-based image fusion with complex wavelets • Article
Information Fusion
Lewis, J.J.; O\'Callaghan, R.J.; Nikolov, S.G.; Bull, D.R.;
Canagarajah, N.
25. Recursive track fusion for multi-sensor surveillance • Article
Information Fusion, Volume 5, Issue 1, 1 March 2004, Pages 23-33
Coraluppi, S.; Carthel, C.
New Volume/Issue is now available on ScienceDirect
Information Fusion
Volume 7, Issue 1, Pages 1-156 (March 2006)
Logic-based Approaches to Information Fusion
Edited by S. Konieczny and E. Grégoire
Editorial
A special issue on logic-based approaches to information fusion
Page 1
Belur V. Dasarathy
Guest Editorial
Logic-based approaches to information fusion
Pages 2-3
Sébastien Konieczny and Éric Grégoire
Regular papers
Logic-based approaches to information fusion
Pages 4-18
Eric Grégoire and Sébastien Konieczny
Social contraction and belief negotiation
Pages 19-34
Richard Booth
An unbiased approach to iterated fusion by weakening
Pages 35-40
Éric Grégoire
Merging operators: Beyond the finite case
Pages 41-60
José Luis Chacón and Ramón Pino Pérez
Social choice theory, belief merging, and strategy-proofness
Pages 61-79
Samir Chopra, Aditya Ghose and Thomas Meyer
Reasoning with multiple-source information in a possibilistic logic
framework
Pages 80-96
Salem Benferhat and Claudio Sossai
Fusion rules for merging uncertain information
Pages 97-134
Anthony Hunter and Weiru Liu
Bipolar possibility theory in preference modeling: Representation,
fusion and optimal solutions
Pages 135-150
Salem Benferhat, Didier Dubois, Souhila Kaci and Henri Prade
Finding FUN in FUsioN—XXII
Page 151
Information Fusion Journal Reviewers 2004 - A Note of Appreciation
Pages 152-153
Articles in Press - available online
Pages 154-155
Vol. 7 No. 1 has just been released. We have a healthy (perhaps too
big!)backlog of accepted papers that are now available online and
awaiting print publication.
Thanks to the number of people who responded to my previous message
seeking reviewers, the backlog of papers needing reviewers has come
down significantly.
Therefore now is a very good time for potential authors contemplating
submission of their work to the Journal to go ahead and submit their
manuscripts since we have been able to clear some of the review
backlog that was recently choking the process.
Thank you for your support to the Journal as authors and reviewers.
Suggestions for special issues that fall within the overall scope of
the Journal are also welcome.
Best Wishes
B.V.Dasarathy
Editor-in-Chief, Information Fusion Journal
Thanks to all those who responded so quickly to my request a couple of
days back. It was indeed gratifying to receive such good response. Of
course, we are still looking for more help. More the merrier!
This call is therefore not only to those who have not reviewed before,
but also to remind those who may have helped previously but have not
been contacted recently, for one reason or another, including loss of
contact information etc.
If you wish to help out again, please contact me with your latest
contact information and a few key words on your current topics of
interest and expertise.
Thanks
B.V.Dasarathy
Due to increasing number of submissions, the Journal is looking for
reviewers in the areas of interest covered by the Information Fusion
Journal. We currently need over 30 new reviewers to meet the demand.
If you are (or any of your colleagues is) interested in helping out,
please reply to d.belur@... with a short bio (and a link to
your home page) and list of topics wherein you feel qualified and
comfortable for helping us with reviews so that we can idenify the
specific manuscripts for your review.
Thanks
B.V.Dasarathy
Editor-in-Chief, Information Fusion
We are a group of 3 full-time researchers and 3
part-times ones, mainly from Italy, who are interested in Financial Time Series Forecasting. We
have been already developing in MatLab financial time-series forecasting
models using Singular Spectrum Analysis, Wavelets Analysis, Fast Fourier
Transform, Pattern Recognition with KNN and SVM classification methods, Kalman
Filter etc. and both linear and non-linear predictive methods (AR, different
types of Neural Networks, etc.) When a large amount of variables optimization
and selection was needed, we implemented genetic algorithms as well.
We are contacting you because we are presently looking
for experienced and knowledgeable researchers who might be willing to
collaborate at the development of financial time series forecasting models
together with us. As long as our collaboration would be based on a mutual
exchange, we would be willing to openly share all the details of our project
including Matlab codes.
The aim of our project is to create complete trading
systems not only to trade personal financial resources but also to establish in
the near future a public investment vehicle (Managed Account or Hedge Fund).
Therefore, there would be eventually the possibility of determining some form
of partnership in the establishment and management of this vehicle.
If you think that you might be interested in knowing
more about ourselves and about our project, we would be more than happy to
share all the details with you. We look forward to hear from you
hopefully soon. Also if you might know other people who could be
interested in our proposal, please feel free to extend our invitation to them
as well.
Hi there,
I am new to DM and more particularly to time series data mining and
I would like to get some help regarding a problem I am facing with
time series analysis.
given a set of n time series as training data, I want to be able to
construct a model that would represent some kind of average of the
given time series. This model would be used to conduct real time
detection of devaite input values.
e.g, if I have 10 time series each of which corresponds to samples
taken every 15 minutes during a period of 24 hours (360 samples for
each TS); I want to be able to detect every 15 minutes whether the
cuurent sample devaites from its corresponding value in the model
constructed from the training data.
And if the deviation is greater than some preconfigured treshold
(maybe %) value, I would like to be able to flag the deviation by
sending an alarm for example.
The challenge with this problem is that the detection of deviations
has to be conducted on a online (real-time) periodic basis , so I
cannot afford to wait till I gather all the 360 samples of today's
measurements before comparing them with the calculaed model.
I would apreciate if you guys can throw in some ideas to help me
tackle this challenging problems. your input would be really
appreciated.
Thanks.
http://ees.elsevier.com/inffus/
Please use this website for all new submissions. For revised versions
of manuscripts previously submited, please use the old website link
that will be forwarded to you in the Email suggesting the revision.
Thank You for your attention to these procedural details.
B.V.Dasarathy
EIC, IF Journal
Hello group members,
I am a new member of this group, coming from the University of Murcia
(Spain). Our research group (AIKE: Artificial Intelligence and
Knowledge Engineering) is working on Temporal Reasoning and Knowledge
Engineering applied to medicine and agriculture. We are interested on
Temporal Data Mining. Our work in this research line is rather
preliminar, just a few algorithms (TSET, TSETmax and a few more in
development) and a method for Temporal Data Abstraction based on
temporal constraints have been proposed and implemented.
We have developed a Clinical Information System for ICU (CH4).
Currently, we are collecting patient data from two hospital. To the
date about 200 patients have been followed during their stay in ICU,
that means a rather low volume of data for testing DM algorithms,
and we are looking for alternative DB to test our developments in the
meanwhile.
Some more information about our group, as well as some papers, are
available at the following link:
http://perseo.dif.um.es/~aike/index_en.html
We would like to share information with people interested in Temporal
Data Mining and to contribute to the site discussions.
By the way, I cordially invite you to attend the next Conference of
the Spanish Association for Artificial Intelligence (CAEPIA'05). You
can find the last call for papers at:
http://www-gsi.dec.usc.es/caepia05/en/index_en.html
Thank you,
Roque Marin
Dpto. de Ingenieria de la Informacion y de las Comunicaciones
Universidad de Murcia. Campus de Espinardo. E-30071. MURCIA. SPAIN
Information Fusion
Volume 6, Issue 3, Pages 187-253 (September 2005)
Fusion of Remotely Sensed Data over Urban Areas
Edited by P. Gamba, O. Hellwich and P. Lombardo
2. A special issue on fusion of remotely sensed data over urban
areas, Page 187, Belur V. Dasarathy
3. Fusion of remotely sensed data over urban areas, Pages 189-192,
Paolo Gamba, Olaf Hellwich and Pierfrancesco Lombardo
4. Thematic and statistical evaluations of five
panchromatic/multispectral fusion methods on simulated PLEIADES-HR
images, Pages 193-212, Florence Laporterie-Déjean, Hélène de
Boissezon, Guy Flouzat and Marie-José Lefèvre-Fonollosa
5. Interband structure modeling for Pan-sharpening of very
high-resolution multispectral images, Pages 213-224, Andrea Garzelli
and Filippo Nencini
6. An IHS and wavelet integrated approach to improve pan-sharpening
visual quality of natural colour IKONOS and QuickBird images, Pages
225-234, Yun Zhang and Gang Hong
7. Automatic normalization of satellite images using unchanged
pixels within urban areas, Pages 235-241, S. Mohammad Ya'allah and M.
Reza Saradjian
8. Comparison of RADARSAT-1 and IKONOS satellite images for urban
features detection, Pages 243-249, Dan Johan Weydahl, Frédéric Bretar
and Pål Bjerke
9. Finding FUN in FUsioN—XX, Page 251, Belur V. Dasarathy
10. Articles in Press - available online, Page 253
Information Fusion
Volume 6, Issue 2, Pages 117-185 (June 2005)
Information fusion in the context of human–machine interfaces
Pages 117-118
Belur V. Dasarathy
Robust image fusion using a statistical signal processing approach
Pages 119-128
Rick S. Blum
Fusion of infrared vision and radar for estimating the lateral
dynamics of obstacles
Pages 129-141
Angelos Amditis, Aris Polychronopoulos, Nikolaos Floudas and Luisa
Andreone
A cluster enseble method for clustering categorical data
Pages 143-151
Zengyou He, Xiaofei Xu and Shengchun Deng
Real-time use of Kohonen's self-organizing maps for threat stabilization
Pages 153-163
Mohamad Khaled Allouche
An extension of statistical decision theory with information theoretic
cost functions to decision fusion: Part II
Pages 165-174
Michael B. Hurley
Parameter estimation for Choquet fuzzy integral based on Takagi–Sugeno
fuzzy model
Pages 175-182
Shihong Yue, Ping Li and Zongxian Yin
Finding FUN in FUsioN—XIX
Page 183
Articles in press - available online
Page 185
Journal: Information Fusion
ISSN : 1566-2535
Volume : 6
Issue : 1 [SPECIAL ISSUE]
Date : Mar-2005
Diversity in Multiple Classifier Systems
Edited by: Ludmila I. Kuncheva
For more information about this journal visit:
http://www.elsevier.com/locate/inffus
______________________________________________________
If you are interested in submitting a paper to this journal visit:
==> http://authors.elsevier.com/journal/inffus
______________________________________________________
Table of Contents:
A special issue on diversity in multiple classifier systems
B.V. Dasarathy
pp 1
Diversity in multiple classifier systems
L.I. Kuncheva
pp 3-4
Diversity creation methods: a survey and categorisation
G. Brown, J. Wyatt, R. Harris, X. Yao
pp 5-20
Diversity measures for multiple classifier system analysis and design
T. Windeatt
pp 21-36
Assessing the predictive accuracy of diversity measures with
domain-dependent, asymmetric misclassification costs
M. Gal-Or, J.H. May, W.E. Spangler
pp 37-48
Ensemble diversity measures and their application to thinning
R.E. Banfield, L.O. Hall, K.W. Bowyer, W.P. Kegelmeyer
pp 49-62
Classifier selection for majority voting
D. Ruta, B. Gabrys
pp 63-81
Diversity in search strategies for ensemble feature selection
A. Tsymbal, M. Pechenizkiy, P. Cunningham
pp 83-98
Creating diversity in ensembles using artificial data
P. Melville, R.J. Mooney
pp 99-111
Finding FUN in FUsioN--XVIII
B.V. Dasarathy
pp 113
List of forthcoming papers
pp 115
ContentsDirect from Elsevier
______________________________________________________
Journal: Information Fusion
ISSN : 1566-2535
Volume : 5
Issue : 4
Date : Dec-2004
For more information about this journal visit:
http://www.elsevier.com/locate/inffus
______________________________________________________
If you are interested in submitting a paper to this journal visit:
http://authors.elsevier.com/journal/inffus
______________________________________________________
Table of Contents:
Editorial board
pp CO2
Full text via ScienceDirect :
http://www.sciencedirect.com/science?
_ob=GatewayURL&_origin=CONTENTS&_method=citationSearch&_piikey=S156625
3504000740&_version=1&md5=9ece99ba151bb4c954a761df7b6f1c3f
A panoramic sampling of avant-garde applications of information
fusion
B.V. Dasarathy
pp 233-238
Full text via ScienceDirect :
http://www.sciencedirect.com/science?
_ob=GatewayURL&_origin=CONTENTS&_method=citationSearch&_piikey=S156625
3504000661&_version=1&md5=b4c89f321d7d516c5eb97cf485111b3c
Fusion of multiple approximate nearest neighbor classifiers for fast
and efficient classification
P. Viswanath, M. Narasimha Murty, S. Bhatnagar
pp 239-250
Full text via ScienceDirect :
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Land use mapping with evidential fusion of features extracted from
polarimetric synthetic aperture radar and hyperspectral imagery
A. Jouan, Y. Allard
pp 251-267
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Evolution strategies based image registration via feature matching
X. Yuan, J. Zhang, B.P. Buckles
pp 269-282
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A practical two-step image registration method for two-dimensional
images
X. Peng, M. Ding, C. Zhou, Q. Ma
pp 283-298
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Space efficient quantization for distributed estimation by a
multi-sensor fusion system
V. Megalooikonomou, Y. Yesha
pp 299-308
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Clustering belief functions based on attracting and conflicting
metalevel evidence using Potts spin mean field theory
J. Schubert
pp 309-318
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Finding FUN in FUsioN--XVII
B.V. Dasarathy
pp 319
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Reviewers (1999-2003) - An acknowledgement
pp 321-324
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Author index
pp 325
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Subject index
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Contents
pp 329-330
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Hello,
This is michelle. I am happy to join in your group. I also invite all
of you yo join in my mining web site,too.
I recently start a new data mining web site. It is MiLiWo (Mining
Linking the World) Data Mining Site. Data mining is already a hot
topic now and applied in any kind of industry. Consequently, we start
this data mining community where you could discuss any topic related
to mining, exchange experiences with each other, get latest news,
view Books introduction, and understand mining tools of public
domains or of vendors. Most specially, we will discuss articles about
data mining application non-periodically from our opinions here. You
could discuss those writings , problems in implementation and suggest
solutions from your experiences with every miner from all over the
world there. Of course, the site will become better since your
coming. We really would like to discuss with you from any kind of
industry.
I sincerely invite all of you to join my web site, Mi Li Wo, which
is located at: http://miliwo.no-ip.com
There you can also join our forum, which is located
at: http://members.lycos.co.uk/datamining
Registration is requested before reading any articles in the forum.
It takes only less than a minute. An email with account activation
instructions will be sent to the email address you provide. Then, you
can activate your account and start a topic right away!
The forum is just started, we will add more articles soon. Please
feel free to post your articles any time. Once our website is online
and connected to this forum, it's for sure that more data miners will
come to this forum.
Sincerely yours,
michelle
The backlog of manuscripts under review process has now reduced with
a couple of special issues having been wrapped up and publication
schedule for the rest of the year firmly in place. Europe folks
(potential authors as well as reviewers) will be getting back to work
soon as well. Accordingly, we are now in a position to process new
submissions expedetiously. It would therefore be a good time for
those planning on seeing their work published in Information Fusion
Journal to submit their manuscripts to get a speedy review.
With the new system, your papers are published electronically online
as soon as they pass the acceptance and proofs stage without having
to wait for the hardcopy publication schedule and the associated
backlogs caused by issue size/pagelimitations.
Also, if you have ideas for special issues for the Journal,please
feel free to contact me at belur@...
Here are some procedural aspects and policy notices regarding
manuscript submission for you information
-------------------------------------------------------------------
The general policy of the Journal requires that the m/s be original
previously unpublished work. Please include with the submission
letter a statement whether this m/s or its equivalent has been
previously published or presented in any forum/form or is currently
under such consideration elsewhere and if so provide full details.
IF AN EARLIER CONFERENCE/WORKSHOP VERSION HAS BEEN PUBLISHED, IT IS
NECESSARY THAT THE MANUSCRIPT IS SUBSTANTIALLY REVISED, EXPANDED AND
DIFFERENT FROM ANY CONFERENCE VERSION AND THE CONFERENCE PUBLICATION
IS INCLUDED AS A REFERENCE. ALSO TO THE EXTENT FEASIBLE IT IS
NECESSARY TO ELIMINATE/MINIMIZE DUPLICATION BETWEEN THIS M/S AND
EARLIER CONFERENCE VERSION. THIS WILL AVOID COPYRIGHT PROBLEMS AS
WELL AS PRESERVE THE JOURNAL REPUTATION AS A VENUE FOR PUBLICATION OF
ORIGINAL WORK OF ARCHIVAL QUALITY. PLEASE SEND DIRECTLY TO THE
EDITOR AN ELECTRONIC COPY OF THE EARLIER RELATED PAPERS IF ANY TO
FACILITATE THE REVIEW PROCESS.
----------------------------------------------------------------------
Information Fusion Journal online Paper Submission Procedure
If you do not already have a profile/account at Elsevier, you should
set up a new profile/account before commencing the e-submission
process. You will need to register via Elsevier's Author Gateway
http://authors.elsevier.com
(When an author has registered once this profile should be used for
all future online submissions - Also, please do not change your user
name in the middle of processing of a submitted paper till it is
published - otherwise revisions etc cannot be made easily). When you
register, you create a username and password, which you will need to
fill in this information every time you want to access/logon to the
system.
In order to submit a manuscript to the journal Information Fusion you
should access the following link:
http://authors.elsevier.com/JournalDetail.html?
PubID=620862&Precis=DESC
Click on the "Online submission Link"
You will be asked to enter your UPC details (Username & Password)
Click on the "submit new paper" button
The submission process is made up of seven steps
Step 1 - Enter the title of the Article
Choose an editor or editorial office (Dr Belur
V. Dasarathy)
Indicate whether the paper will be submitted
in LaTex or as a standard Word processing format
Step 2 - Upload or type in a cover letter
You will need to upload the source file in the correct format
i.e. .doc or latex, that the source file will need to have the
figures/graphics embedded.
Step 3 - The system will generate a PDF file from the
source file.
The PDF file is used for reviewing purposes only and it is the source
file that is used by production for the typesetting of your paper.
Step 4 - You will also need to enter the quantity of
figures/graphics contained in his manuscript at step four of the
online submission and then upload these figure/graphic files
separately.
Step 5 - You will choose how the figures should appear in
the printed journal and the author can also check the colour prices
here
Step 6 - Here you will types in the total number of
supplementary files, please advise the author that it is not
mandatory to upload supplementary files.
Step 7- this is the confirmation page it gives an
overview of all the submission details. Then click once on
the "submit" button to submit the paper to the editor/editorial
office. After clicking this button automated emails are sent to the
author and Editor.
Please note that should you ever require any assistance please note
that our Author Support department at authorsupport@... will
be happy to help.
Information Fusion
Volume 5, Issue 3, Pages 155-231 (September 2004)
http://www.sciencedirect.com/science/issue/6618-2004-999949996-511537
NOTE: If the URLs in this email are not active hyperlinks, copy and
paste the URL into the address/location box in your browser.
======================================================================
Information Fusion Volume 5, Issue 3, Pages 155-231 (September 2004)
TABLE OF CONTENTS
Does length matter?, Pages 155-156
Belur V. Dasarathy
Distributed M-ary hypothesis testing with binary local decisions,
Pages 157-167
Xiaoxun Zhu, Yingqin Yuan, Chris Rorres and MosheKam
Spatio-temporal multi-mode information management for moving target
detection, Pages 169-178
Frederic Dambreville and Jean-Pierre Le Cadre
On aggregating belief decision trees, Pages 179-188
Patrick Vannoorenberghe
Formalizing classes of information fusion systems, Pages 189-202
Mieczyslaw M. Kokar, Jerzy A. Tomasik and Jerzy Weyman
Evidential segmentation scheme of multi-echo MR images for the
detection of brain tumors using neighborhood information, Pages 203-
216
A. -S. Capelle, O. Colot and C. Fernandez-Maloigne
Visual acuity of vision tested by fuzzy logic: An application in
ophthalmology as a step towards a telemedicine project, Pages 217-230
A. Taleb-Ahmed, A. Bigand, V. Lethuc and P. M. Allioux
Finding FUN in FUsioN--XVI, Page 231
Belur V. Dasarathy