Machine Learning and Data Mining

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Machine Learning and Data Mining

in Pattern Recognition


4th International Conference

MLDM 2005


Program 09. 07.


11. 07. 2005



Organized by:



Institute of Computer Vision and
Applied Computer Sciences,


Lei
pzig/Germany




2

Welcome


We meet again in front of the stature of
Gottfried Wilhelm von Leibniz

at the city of
Leipzig. Leibniz, a famous son of Leipzig, planed automatic logical inference using
symbolic computation

and

aimed
to collate all

human knowledge
.

Today, artificial
intelligence deals with large amount of data and knowledge and finds new
information using machine learning and data mining in computer. Machine learning
and data mining are irreplaceable subject and tools for the theory of pattern
reco
gnition and application of pattern recognition such as bioinformatics and data
retrieval
.

This is the fourth edition of MLDM in Pattern Recognition which is the main event
of Technical Committee 17 in International Association in Pattern Recognition
succee
ded from 1999, 2001, and 2003, which started out as a workshop and was
continued as a conference in 2003. Today, there are many international meetings
which are titled machine learning and data mining, whose topics are text mining,
knowledge discovery, and

applications. This meeting from the first time has focused
on aspects of machine learning and data mining in pattern recognition problems. We
planed to re
-
organize

classical and well
-
established pattern recognition paradigms
from
viewpoints

of machine lea
rning and data mining. Though it was a challenging
program in late ‘90’s, the idea has brought new starting points in pattern recognition
and effects to the other areas suc
h as cognitive computer vision.

In this edition the
organizing

committee had receive
d 103 submissions from 20
countries. After peer review process, we have accepted 58 papers for presentation.
We deeply thank members of program committees and reviewers, who finished hard
task to review papers form broad areas and wide range of application
s. We also
thank members of Institute of Applied Computer Sciences, Leipzig, Germany, who
handed the conference as secretariat. We appreciate the help and understanding of
the editorial staff at Springer Verlag, and in particular Alfred Hofmann, who
suppor
ted the publication of th
ese proceedings in LNAI series.

Last, but not least, we wish to thank all the speakers and participants who
contributed to

the success of the conference.




July 2005, Petra Perner and Atsushi Imiya






3

Saturday, 09.07.2005



8.00 am

Registration



8.45 am

Welcome

Petra Perner
,
Institute of Computer Vision and Applied Computer Sciences, IBaI Leipzig, Germany



Feature Grouping, Discretization, Selection and Transformation


Session Chair: A. Imiya



9.00 am

Feature Selec
tion Method Using Preferences Aggregation

G. Legrand and N. Nicoloyannis



9.20 am

Ranked Modelling with Feature Selection Based on the CPL Criterion Functions

L. Bobrowski



9.40 am

A Grouping Method for Categorical Attributes Having Very Large Number

of Values

M. Boullé



10.00 am

Unsupervised Learning of Visual Feature Hierarchies

F. Scalzo and J. Piater



10.20 am

Coffee Break



Feature Grouping, Discretization, Selection and Transformation

Session Chair: P. Perner



10.50 am

Multivariate D
iscretization by Recursive Supervised Bipartition of Graph

S. Ferrandiz and M. Boullé



11.10 am

CorePhrase: Keyphrase Extraction for Document Clustering

K. M. Hammouda, M. S. Kamel, D. N. Matute



11.30 am

A New Multidimensional Feature Transformation

for Linear Classifiers and Its Applications

E. Bak



11.50 am

Coffee Break



Subspace Methods

Session Chair: L. Bobrowski



12.00 am

The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets

I. Takigawa, M. Kudo, A. Nak
amura



0.20 pm

SSC: Statistical Subspace Clustering

I. Candillier, I. Tellier, F. Torre, O. Bousquet



0.40 pm

Understanding Patterns with Different Subspace Classification

G. Szepannek, K. Luebke, C. Weihs



1.00 pm

Lunch



Applications in Medici
ne


Session Chair: V. Kovalev



2.30 pm

Comparison of FLDA, MLP and SVM in Diagnosis of Lung Nodule

A. C. Silva, A. C. de Paiva, A. C. M. de Oliveira



2.50 pm

Prediction of Secondary Protein Structure Content from Primary Sequence Alone
-

a Feature S
election Based Approach

L. Kurgan and L. Homaeian


4

3.10 pm

Improved MRI Mining by Integrating Support Vector Machine Priors in the
Bayesian Restoration

D. A. Karras, Chalkis, B. G. Mertzios, D. Graveron
-
Demilly, C. van Ormondt



3.30 pm

Alternative Clust
ering by Utilizing Multi
-
Objective Genetic Algorithm with
Linked
-
List Based Chromosome Encoding

J. Du, R. Alhajj, K. Barker, E. E. Korkmaz



3.50 pm

Coffee Break



Neural Methods


Session Chair: A. Krzyzak



4.20 pm

Comparative Analysis of Genetic A
lgorithm, Simulated Annealing and Cutting
Angle Method for Artificial Neural Networks

R. Ghosh, M. Ghosh, J. Yearwood, A. Bagirov



4.40 pm

A
C
omprehensible SOM
-
based Scoring System

I. Huysmans, B. Baesens, J. Vanthienen



5.00 pm

Determining Regulariz
ation Parameters for Derivative Free Neural Learning

R. Ghosh, M. Ghosh, J. Yearwood, A. Bagirov



5.20 pm

Coffee Break



Applications in Medicine


Session Chair: B. G. Mertzios



5.30 pm

Diagnosis of Lung Nodule Using Reinforcement Learning and Geo
metric Measures

A. C. Silva, V. R. da Silva Junior, A. de Almeida Neto, A. C. de Paiva



5.50 pm

Automatic Clinical Image Segmentation using Pathological Modelling, PCA and
SVM

Sh. Li, T. Fevens, A. Krzyzak, S. Li



6.10 pm

Iris Recognition Algorithm B
ased on Point Covering of High
-
Dimensional Space
and Neural Network

W. Cao, J. Hu, G. Xiao, Sh. Wang



6.30 pm

End of 1
st

Day



Sunday, 10.07.2005



8.45 am

Registration



Clustering: Basics


Session Chair: M. Boullé



9.00 am

Using Clustering t
o Learn Distance Functions for Supervised Similarity Assessment

Ch. F. Eick, A. Rouhana, A. Bagherjeiran, R. Vilalta



9.20 am

Linear Manifold Clustering

R. Harpaz and R. Haralick



9.40 am

Universal Clustering with Regularization in Probabilistic Spac
e

V. Nikulin and A. J. Smola




5

10.00 am

Acquisition of Concept Descriptions by Conceptual Clustering

S. Jänichen and P. Perner



10.20 am

Coffee Break



Classification and Model Estimation


Session Chair: G. Giacinto



10.50 am

Incremental Classif
ication Rules Based on Association Rules Using Formal
Concept Analysis

A. Gupta, N. Kumar, V. Bhatnagar



11.10 am

On ECOC as Binary Ensemble Classifiers

I. Ko and E. Kim



11.30 am

Parameter Inference of Cost
-
Sensitive Boosting Algorithms

Y. Sun, A. K
. C. Wong, Y. Wang



11.50 am

Coffee Break



12.00 am

MML
-
Based Approach for Finite Dirichlet Mixture Estimation and Selection

N. Bouguila and D. Ziou



0.20 pm

Principles of Multi
-
Kernel Data Mining

O. Seredin, V. Mottl, O. Krasotkina, I. Muchnik



0.40 am

Finite Mixture Models with Negative Components

B. Zhang and Ch. Zhang



1.00 pm

Lunch



Applications of Clustering


Session Chair: Bon K. Sy



2.30 pm

On the Clustering of Large Dynamic Datasets

W. Sia and M. Lazarescu



2.50 pm

Birds of

a Feather Surf Together: Using Clustering Methods to Improve
Navigation Prediction from Internet Log Files

I. Halvey, M. T. Keane, B. Smyth



3.10 pm

Alarm Clustering for Intrusion Detection Systems in Computer Networks

G. Giacinto, R. Perdisci, F. Roli



3.30 pm

Clustering Document Images Using Graph Summaries

E. Barbu, P. Heroux, S. Adam, E. Trupin



3.50 pm

Coffee Break



Mining Images and Texture

Session Chair: A. Imiya



4.20 pm

Optimising the Choice of Colours of an Image Database for Dic
hromats

V. Kovalev and M. Petrou



4.40 pm

Hierarchical Partitions for Content Image Retrieval from Large
-
Scale Database

D. Kinoshenko, V. Mashtalir, E. Yegorova, V. Vinarsky






6

5.00 pm

An Approach to Mining Picture Objects Based on Textual Cues

B. A
degorite, O. A. Basir, M. S. Kamel, K. B. Shaban



5.20 pm

Coffee Break



Speech Analysis

Session Chair: A. Krzyzak


5.30 pm

An Evidential Reasoning Approach to Weighted Combination of Classifiers for
Word Sense Disambiguation

A. Le, V. N. Huynh, A
. Shimazu



5.50 pm

Neural Expert Model Applied to Phonemes Recognition

H. Bahi and M. Sellami



6.10 pm

End of 2
nd

Day



7.00 pm

Banquet Ratskeller



Monday, 11.07.2005



8.45 am

Registration



Mining Images in Computer Vision

Session Chair:

M. Haraguchi



9.00 am

Support Vector Machine Experiments for Road Recognition in High Resolution Images

J. Y. Lai, A. Sowmya, J. Trinder



9.20 am

Cost Integration in Multi
-
Step Viewpoint Selection for Object Recognition

Ch. Derichs, H. Niemann, F. D
einzer



9.40 am

Autonomous Vehicle Steering based on Evaluative Feedback by Reinforcement
Learning

K.
-
D. Kuhnert and M. Krödel



10.00 am

An Automatic Face Recognition System in the Near Infrared Spectrum

Sh. Zhao and R.
-
R. Grigat



10.20 am

Coffee
Break



Time Series and Sequential Pattern Mining


Session Chair:
D. Ziou



10.50 am

Embedding Time Series Data for Classification

A. Hayashi, N. Suematsu, Y. Mizuhara



11.10 am

Analysis of Time Series of Graphs: Prediction of Node Presence by Mean
s of
Decision Tree Learning

H. Bunke, Ch. Irniger, M. Kraetzl, P. Dickinson



11.30 am

Disjunctive Sequential Patterns on Single Data Sequence and its Anti
-
Monotonicity

K. Shimizu and T. Miura



11.50 am

Coffee Break








7

Time Series and Sequentia
l Pattern Mining

Session Chair: M. Haraguchi



12.00 am

Mining Expressive Temporal Associations from Complex Data

K. A. Pray and C. Ruiz



0.20 pm

Statistical Supports for Frequent Itemsets on Data Streams

P.
-
A. Laur, J.
-
E. Symphor, R. Nock, O. Poncele
t



0.40 pm

Lunch



Text Mining
Session Chair: B. G. Mertzios



2.10 pm

Pattern Mining Across Domain
-
Specific Text Collections

L. Gillam and K. Ahmad



2.30 pm

Low
-
level Cursive Word Representation Based on Geometric Decomposition

J.
-
X. Dong, D.
Ponson, A. Krzyzak, Ch. Y. Suen



2.50 pm

Text Classification Using Small Number of Features

M. Makrehchi and M. S. Kamel



3.10 pm

Coffee Break



Aspects of Data Mining
Session Chair: P. Perner



3.40 pm

Signature
-
based Approach for Intrusion De
tection

Bon K. Sy



4.00 pm

Data Mining on Crash Simulation Data

A. Kuhlmann, R.
-
M. Vetter, C.
-
A. Thole, Ch. Lübbing



4.20 pm

Discovery of Hidden Correlations in a Local Transaction Database based on
Differences of Correlations

T. Taniguchi, M. Haragu
chi, Y. Okubo



4.40 pm

An Integrated Approach for Mining Meta
-
Rules

F. Ye, J. Wang, H. Chen, T. Huang, L. Tao, Sh. Wu



5.00 pm

Coffee Break



Mining Motion from Sequence
Session Chair: V. Kovalev



5.10 pm

Dominant Plane Detection Using Optical

Flow and Independent Component Analysis

I. Ohnishi and A. Imiya



5.30 pm

An New Approach to Human Motion Sequence Recognition with Application to
Diving Actions

Sh. Xiang, Ch. Zhang, X. Chen, N. Lu



5.50 pm

Activity and Motion Detection Based on Mea
suring Texture Change

L. J. Latecki, R. Miezianko, D. Pokrajac



6.10 pm

Diskussion and Fair Well



6.20 pm

End of the Conference















Institute of Computer Vision

and Applied Computer Sciences


Körnerstraße 10

0
4107 Leipzig/Germany



Phone:

+49(0341)86 12 273

FAX:

+49(0341)86 12
2
75



E
-
mail:

ibaiperner@aol.com

Homepage:

www.ibai
-
institut
.de