Petra Perner, Atsushi Imiya
Proceedings of the Fourth International Conference on Machine Learning and Data Mining in Pattern Recognition
MLDM, 2005.

@proceedings{MLDM-2005,
	address       = "Leipzig, Germany",
	editor        = "Petra Perner and Atsushi Imiya",
	isbn          = "3-540-26923-1",
	publisher     = "{Springer International Publishing}",
	series        = "{Lecture Notes in Computer Science}",
	title         = "{Proceedings of the Fourth International Conference on Machine Learning and Data Mining in Pattern Recognition}",
	volume        = 3587,
	year          = 2005,
}

Contents (68 items)

12 ×#clustering
12 ×#using
11 ×#mining
9 ×#approach
8 ×#classification
6 ×#image
6 ×#multi
6 ×#recognition
5 ×#analysis
5 ×#learning

MLDM-2005-KoK #classification #on the

On ECOC as Binary Ensemble Classifiers (JK, EK), pp. 1–10.

MLDM-2005-GuptaKB #classification #concept analysis #incremental #using

Incremental Classification Rules Based on Association Rules Using Formal Concept Analysis (AG, NK, VB), pp. 11–20.

MLDM-2005-SunWW #algorithm #parametricity

Parameter Inference of Cost-Sensitive Boosting Algorithms (YS, AKCW, YW), pp. 21–30.

MLDM-2005-ZhangZ #component #finite #modelling

Finite Mixture Models with Negative Components (BZ, CZ), pp. 31–41.

MLDM-2005-BouguilaZ #approach #estimation #finite

MML-Based Approach for Finite Dirichlet Mixture Estimation and Selection (NB, DZ), pp. 42–51.

MLDM-2005-MottlKSM #data mining #kernel #mining #multi

Principles of Multi-kernel Data Mining (VM, OK, OS, IBM), pp. 52–61.

MLDM-2005-GhoshGYB #algorithm #analysis #comparative #network #search-based

Comparative Analysis of Genetic Algorithm, Simulated Annealing and Cutting Angle Method for Artificial Neural Networks (RG, MG, JY, AMB), pp. 62–70.

MLDM-2005-GhoshGYB05a #learning #parametricity

Determining Regularization Parameters for Derivative Free Neural Learning (RG, MG, JY, AMB), pp. 71–79.

MLDM-2005-HuysmansBV

A Comprehensible SOM-Based Scoring System (JH, BB, JV), pp. 80–89.

MLDM-2005-TakigawaKN #classification #combinator #product line #set #subclass

The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets (IT, MK, AN), pp. 90–99.

MLDM-2005-CandillierTTB #clustering #named #statistics

SSC: Statistical Subspace Clustering (LC, IT, FT, OB), pp. 100–109.

MLDM-2005-SzepannekLW #classification #comprehension

Understanding Patterns with Different Subspace Classification (GS, KL, CW), pp. 110–119.

MLDM-2005-EickRBV #assessment #clustering #distance #similarity #using

Using Clustering to Learn Distance Functions for Supervised Similarity Assessment (CFE, AR, AB, RV), pp. 120–131.

MLDM-2005-HaralickH #clustering #linear

Linear Manifold Clustering (RMH, RH), pp. 132–141.

MLDM-2005-NikulinS #clustering #probability

Universal Clustering with Regularization in Probabilistic Space (VN, AJS), pp. 142–152.

MLDM-2005-JanichenP #clustering #concept

Acquisition of Concept Descriptions by Conceptual Clustering (SJ, PP), pp. 153–162.

MLDM-2005-SiaL #clustering #dataset #scalability #using

Clustering Large Dynamic Datasets Using Exemplar Points (WS, MML), pp. 163–173.

MLDM-2005-HalveyKS #clustering #internet #navigation #predict #using

Birds of a Feather Surf Together: Using Clustering Methods to Improve Navigation Prediction from Internet Log Files (MH, MTK, BS), pp. 174–183.

MLDM-2005-GiacintoPR #clustering #detection #network

Alarm Clustering for Intrusion Detection Systems in Computer Networks (GG, RP, FR), pp. 184–193.

MLDM-2005-BarbuHAT #clustering #documentation #graph #image #summary #using

Clustering Document Images Using Graph Summaries (EB, PH, SA, ÉT), pp. 194–202.

MLDM-2005-LegrandN #feature model #using

Feature Selection Method Using Preferences Aggregation (GL, NN), pp. 203–217.

MLDM-2005-Bobrowski #feature model #modelling

Ranked Modelling with Feature Selection Based on the CPL Criterion Functions (LB), pp. 218–227.

MLDM-2005-Boulle #category theory #scalability

A Grouping Method for Categorical Attributes Having Very Large Number of Values (MB), pp. 228–242.

MLDM-2005-ScalzoP #learning #visual notation

Unsupervised Learning of Visual Feature Hierarchies (FS, JHP), pp. 243–252.

MLDM-2005-FerrandizB #graph #multi #recursion

Multivariate Discretization by Recursive Supervised Bipartition of Graph (SF, MB), pp. 253–264.

MLDM-2005-HammoudaMK #clustering #documentation #named

CorePhrase: Keyphrase Extraction for Document Clustering (KMH, DNM, MSK), pp. 265–274.

MLDM-2005-Bak #classification #linear #multi

A New Multidimensional Feature Transformation for Linear Classifiers and Its Applications (EB), pp. 275–284.

MLDM-2005-SilvaPO #comparison

Comparison of FLDA, MLP and SVM in Diagnosis of Lung Nodule (ACS, ACdP, ACMdO), pp. 285–294.

MLDM-2005-SilvaJNP #geometry #learning #metric #using

Diagnosis of Lung Nodule Using Reinforcement Learning and Geometric Measures (ACS, VRdSJ, AdAN, ACdP), pp. 295–304.

MLDM-2005-CaoHXW #algorithm #network #recognition

Iris Recognition Algorithm Based on Point Covering of High-Dimensional Space and Neural Network (WC, JH, GX, SW), pp. 305–313.

MLDM-2005-LiFKL #automation #image #modelling #segmentation #using

Automatic Clinical Image Segmentation Using Pathological Modelling, PCA and SVM (SL, TF, AK, SL), pp. 314–324.

MLDM-2005-KarrasMGO #mining

Improved MRI Mining by Integrating Support Vector Machine Priors in the Bayesian Restoration (DAK, BGM, DGD, DvO), pp. 325–333.

MLDM-2005-KurganH #approach #feature model #predict #sequence

Prediction of Secondary Protein Structure Content from Primary Sequence Alone — A Feature Selection Based Approach (LAK, LH), pp. 334–345.

MLDM-2005-DuKAB #algorithm #clustering #encoding #multi #search-based

Alternative Clustering by Utilizing Multi-objective Genetic Algorithm with Linked-List Based Chromosome Encoding (JD, EEK, RA, KB), pp. 346–355.

MLDM-2005-HayashiMS #classification

Embedding Time Series Data for Classification (AH, YM, NS), pp. 356–365.

MLDM-2005-BunkeDIK #analysis #graph #learning #predict

Analysis of Time Series of Graphs: Prediction of Node Presence by Means of Decision Tree Learning (HB, PJD, CI, MK), pp. 366–375.

MLDM-2005-ShimizuM #anti #sequence

Disjunctive Sequential Patterns on Single Data Sequence and Its Anti-monotonicity (KS, TM), pp. 376–383.

MLDM-2005-PrayR #mining

Mining Expressive Temporal Associations from Complex Data (KAP, CR), pp. 384–394.

MLDM-2005-LaurSNP #data type #statistics

Statistical Supports for Frequent Itemsets on Data Streams (PAL, JES, RN, PP), pp. 395–404.

MLDM-2005-KuhnertK #feedback #learning

Autonomous Vehicle Steering Based on Evaluative Feedback by Reinforcement Learning (KDK, MK), pp. 405–414.

MLDM-2005-DerichsDN #integration #multi #recognition

Cost Integration in Multi-step Viewpoint Selection for Object Recognition (CD, FD, HN), pp. 415–425.

MLDM-2005-LaiST #image #recognition

Support Vector Machine Experiments for Road Recognition in High Resolution Images (JYL, AS, JT), pp. 426–436.

MLDM-2005-ZhaoG #automation #recognition

An Automatic Face Recognition System in the Near Infrared Spectrum (SZ, RRG), pp. 437–444.

MLDM-2005-KinoshenkoMYV #database #image #retrieval #scalability

Hierarchical Partitions for Content Image Retrieval from Large-Scale Database (DK, VM, EY, VV), pp. 445–455.

MLDM-2005-KovalevP #database #image #optimisation

Optimising the Choice of Colours of an Image Database for Dichromats (VAK, MP), pp. 456–465.

MLDM-2005-AdegoriteBKS #approach #mining

An Approach to Mining Picture Objects Based on Textual Cues (AIA, OAB, MSK, KBS), pp. 466–475.

MLDM-2005-LateckiMP #detection #process

Activity and Motion Detection Based on Measuring Texture Change (LJL, RM, DP), pp. 476–486.

MLDM-2005-XiangZCL #approach #recognition #sequence

A New Approach to Human Motion Sequence Recognition with Application to Diving Actions (SX, CZ, XC, NL), pp. 487–496.

MLDM-2005-OhnishiI #analysis #component #detection #independence #using

Dominant Plane Detection Using Optical Flow and Independent Component Analysis (NO, AI), pp. 497–506.

MLDM-2005-BahiS #recognition

Neural Expert Model Applied to Phonemes Recognition (HB, MS), pp. 507–515.

MLDM-2005-LeHS #ambiguity #approach #classification #reasoning #word

An Evidential Reasoning Approach to Weighted Combination of Classifiers for Word Sense Disambiguation (CAL, VNH, AS), pp. 516–525.

MLDM-2005-Sy #approach #detection

Signature-Based Approach for Intrusion Detection (BKS), pp. 526–536.

MLDM-2005-TaniguchiHO #correlation #database #difference #transaction

Discovery of Hidden Correlations in a Local Transaction Database Based on Differences of Correlations (TT, MH, YO), pp. 537–548.

MLDM-2005-YeWWCHT #approach #mining

An Integrated Approach for Mining Meta-rules (FY, JW, SW, HC, TH, LT), pp. 549–557.

MLDM-2005-KuhlmannVLT #data mining #mining #simulation

Data Mining on Crash Simulation Data (AK, RMV, CL, CAT), pp. 558–569.

MLDM-2005-GillamA #mining

Pattern Mining Across Domain-Specific Text Collections (LG, KA), pp. 570–579.

MLDM-2005-MakrehchiK #classification #using

Text Classification Using Small Number of Features (MM, MSK), pp. 580–589.

MLDM-2005-DongKSP #composition #geometry #low level #representation #word

Low-Level Cursive Word Representation Based on Geometric Decomposition (JxD, AK, CYS, DP), pp. 590–599.

MLDM-2005-FerrandizB05a #dataset #evaluation

Supervised Evaluation of Dataset Partitions: Advantages and Practice (SF, MB), pp. 600–609.

MLDM-2005-SilvaK #clustering #distributed

Inference on Distributed Data Clustering (JCdS, MK), pp. 610–619.

MLDM-2005-SharmaVTV #approach #database #mining #multi #novel

A Novel Approach of Multilevel Positive and Negative Association Rule Mining for Spatial Databases (LKS, OPV, UST, RV), pp. 620–629.

MLDM-2005-XiaWZL #data mining #mining #modelling #random

Mixture Random Effect Model Based Meta-analysis for Medical Data Mining (YX, SW, CZ, SL), pp. 630–640.

MLDM-2005-HamanoS #analysis #semantics

Semantic Analysis of Association Rules via Item Response Theory (SH, MS), pp. 641–650.

MLDM-2005-VermaVV #approach #mining #using

Temporal Approach to Association Rule Mining Using T-Tree and P-Tree (KV, OPV, RV), pp. 651–659.

MLDM-2005-HanCY #analysis #component #feature model #image #independence #using

Aquaculture Feature Extraction from Satellite Image Using Independent Component Analysis (JGH, KHC, YKY), pp. 660–666.

MLDM-2005-KotsiantisTRP #modelling

Modeling the Organoleptic Properties of Matured Wine Distillates (SBK, GET, CR, PEP), pp. 667–673.

MLDM-2005-KotsiantisTP #estimation #random

Bagging Random Trees for Estimation of Tissue Softness (SBK, GET, PEP), pp. 674–681.

MLDM-2005-BichindaritzA #concept #mining

Concept Mining for Indexing Medical Literature (IB, SA), pp. 682–691.