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1.

図書
図書
1. Machine learning and data mining in pattern recognition : first International Workshop, MLDM '99, Leipzig, Germany, September 16-18, 1999 : proceedings
Petra Perner, Maria Petrou (eds.)
出版情報: Berlin ; Tokyo : Springer, c1999  viii, 215 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1715 . Lecture notes in artificial intelligence
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目次情報: 続きを見る
Invited Papers
Learning in Pattern Recognition / M. Petrou
Advances in Predictive Data Mining Methods / S.J. Hong ; S.M. Weiss
Neural Networks Applied to Image Processing and Recognition
Multi-valued and Universal Binary Neurons: Learning Algorithms, Application to Image Processing and Recognition / I. N. Aizenberg ; N. N. Aizenberg ; G.A. Krivosheev
A Dynamics of the Hough Transform and Artificial Neural Networks / A. Imiya ; K. Kawamoto
Applications of Cellular Neural Networks for Shape from Shading Problem / M. Milanova ; P. E. M. Almeida ; J. Okamoto ; M. G. Simoes
Learning in Image Pre-Processing and Segmentation
Unsupervised Learning of Local Mean Grey Values for Image Pre-Processing / H. Jahn
Neural Networks in MR Image Estimation from Sparsely Sampled Scans / M. Reczko ; D.A. Karras ; V. Mertzios ; D. Graveron-Demilly ; D. van Ormondt
Extraction of Local Structural Features in Images by Using a Multi-scale Relevance Function / R. M. Palenichka ; M. A. Volgin
Image Retrieval
Independent Feature Analysis for Image Retrieval / J. Peng ; B. Bhanu
Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval / I. King ; T.-K. Lau
Classification and Image Interpretation
Automatic Design of Multiple Classifier Systems by Unsupervised Learning / G. Giacinto ; F. Roli
A Comparison between Neural Networks and Decision Trees / C. Jacobsen ; U. Zscherpel ; P. Perner
Symbolic Learning and Neural Networks in Document Processing
Symbolic Learning Techniques in Paper Document Processing / O. Altamura ; F. Esposito ; F. A. Lisi ; D. Malerba
Recognition of Printed Music Score / T. Beran ; T. Macek
Data Mining
Reproductive Process-Oriented Data Mining From Interactions between Human and Complex ArtifactSystem / T. Sawaragi
Generalized Fuzzy Aggregation Operators / K. R. Sasikala
A Data Mining Application for Monitoring Environmental Risks / A. Scaringella
Author Index
Invited Papers
Learning in Pattern Recognition / M. Petrou
Advances in Predictive Data Mining Methods / S.J. Hong ; S.M. Weiss
2.

図書
図書
2. Advances in structural and syntactical pattern recognition : 6th International Workshop, SSPR '96, Leipzig, Germany, August 20-23, 1996 : proceedings
Petra Perner, Patrick Wang, Azriel Rosenfeld, (eds.)
出版情報: Berlin : Springer, c1996  x, 392 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1121
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3.

図書
図書
3. Machine learning and data mining in pattern recognition : third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003 : proceedings
Petra Perner, Azriel Rosenfeld (eds.)
出版情報: Berlin ; Tokyo : Springer, c2003  xii, 440 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2734 . Lecture notes in artificial intelligence
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4.

図書
図書
4. Data mining on multimedia data
Petra Perner
出版情報: Berlin ; Tokyo : Springer, c2002  x, 131 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2558
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目次情報: 続きを見る
Introduction / 1：
What Is Data Mining? / 1.1：
Some More Real-World Applications / 1.2：
Data Mining Methods - An Overview / 1.3：
Basic Problem Types / 1.3.1：
Prediction / 1.3.2：
Classification / 1.3.2.1：
Regression / 1.3.2.2：
Knowlegde Discovery / 1.3.3：
Deviation Detection / 1.3.3.1：
Cluster Analysis / 1.3.3.2：
Visualization / 1.3.3.3：
Association Rules / 1.3.3.4：
Segmentation / 1.3.3.5：
Data Mining Viewed from the Data Side / 1.4：
Types of Data / 1.5：
Conclusion / 1.6：
Data Preparation / 2：
Data Cleaning / 2.1：
Handling Outlier / 2.2：
Handling Noisy Data / 2.3：
Missing Values Handling / 2.4：
Coding / 2.5：
Recognition of Correlated or Redundant Attributes / 2.6：
Abstraction / 2.7：
Attribute Construction / 2.7.1：
Images / 2.7.2：
Time Series / 2.7.3：
Web Data / 2.7.4：
Conclusions / 2.8：
Methods for Data Mining / 3：
Decision Tree Induction / 3.1：
Basic Principle / 3.1.1：
Terminology of Decision Tree / 3.1.2：
Subtasks and Design Criteria for Decision Tree Induction / 3.1.3：
Attribute Selection Criteria / 3.1.4：
Information Gain Criteria and Gain Ratio / 3.1.4.1：
Gini Function / 3.1.4.2：
Discretization of Attribute Values / 3.1.5：
Binary Discretization / 3.1.5.1：
Multi-interval Discretization / 3.1.5.2：
Discretization of Categorical or Symbolical Attributes / 3.1.5.3：
Pruning / 3.1.6：
Overview / 3.1.7：
Cost-Complexity Pruning / 3.1.8：
Some General Remarks / 3.1.9：
Summary / 3.1.10：
Case-Based Reasoning / 3.2：
Background / 3.2.1：
The Case-Based Reasoning Process / 3.2.2：
CBR Maintenance / 3.2.3：
Knowledge Containers in a CBR System / 3.2.4：
Design Consideration / 3.2.5：
Similarity / 3.2.6：
Formalization of Similarity / 3.2.6.1：
Similarity Measures / 3.2.6.2：
Similarity Measures for Images / 3.2.6.3：
Case Description / 3.2.7：
Organization of Case Base / 3.2.8：
Learning in a CBR System / 3.2.9：
Learning of New Cases and Forgetting of Old Cases / 3.2.9.1：
Learning of Prototypes / 3.2.9.2：
Learning of Higher Order Constructs / 3.2.9.3：
Learning of Similarity / 3.2.9.4：
Clustering / 3.2.10：
General Comments / 3.3.1：
Distance Measures for Metrical Data / 3.3.3：
Using Numerical Distance Measures for Categorical Data / 3.3.4：
Distance Measure for Nominal Data / 3.3.5：
Contrast Rule / 3.3.6：
Agglomerate Clustering Methods / 3.3.7：
Partitioning Clustering / 3.3.8：
Graphs Clustering / 3.3.9：
Similarity Measure for Graphs / 3.3.10：
Hierarchical Clustering of Graphs / 3.3.11：
Conceptual Clustering / 3.3.12：
Concept Hierarchy and Concept Description / 3.4.1：
Category Utility Function / 3.4.3：
Algorithmic Properties / 3.4.4：
Algorithm / 3.4.5：
Conceptual Clustering of Graphs / 3.4.6：
Notion of a Case and Similarity Measure / 3.4.6.1：
Evaluation Function / 3.4.6.2：
Prototype Learning / 3.4.6.3：
An Example of a Learned Concept Hierarchy / 3.4.6.4：
Evaluation of the Model / 3.4.7：
Error Rate, Correctness, and Quality / 3.5.1：
Sensitivity and Specifity / 3.5.2：
Test-and-Train / 3.5.3：
Random Sampling / 3.5.4：
Cross Validation / 3.5.5：
Feature Subset Selection / 3.5.6：
Feature Subset Selection Algorithms / 3.6.1：
The Wrapper and the Filter Model for Feature Subset Selection / 3.6.2.1：
Feature Selection Done by Decision Tree Induction / 3.6.3：
Feature Subset Selection Done by Clustering / 3.6.4：
Contextual Merit Algorithm / 3.6.5：
Floating Search Method / 3.6.6：
Applications / 3.6.7：
Controlling the Parameters of an Algorithm/Model by Case-Based Reasoning / 4.1：
Modelling Concerns / 4.1.1：
Case-Based Reasoning Unit / 4.1.2：
Management of the Case Base / 4.1.3：
Case Structure and Case Base / 4.1.4：
Non-image Information / 4.1.4.1：
Image Information / 4.1.4.2：
Image Similarity Determination / 4.1.5：
Image Similarity Measure 1 (ISim_1) / 4.1.5.1：
Image Similarity Measure 2 (iSIM_2) / 4.1.5.2：
Comparision of ISim_1 and ISim_2 / 4.1.5.3：
Segmentation Algorithm and Segmentation Parameters / 4.1.6：
Similarity Determination / 4.1.7：
Overall Similarity / 4.1.7.1：
Similarity Measure for Non-image Information / 4.1.7.2：
Similarity Measure for Image Information / 4.1.7.3：
Knowledge Acquisition Aspect / 4.1.8：
Mining Images / 4.1.9：
Preparing the Experiment / 4.2.1：
Image Mining Tool / 4.2.3：
The Application / 4.2.4：
Brainstorming and Image Catalogue / 4.2.5：
Interviewing Process / 4.2.6：
Setting Up the Automatic Image Analysis and Feature Extraction Procedure / 4.2.7：
Image Analysis / 4.2.7.1：
Feature Extraction / 4.2.7.2：
Collection of Image Descriptions into the Data Base / 4.2.8：
The Image Mining Experiment / 4.2.9：
Review / 4.2.10：
Using the Discovered Knowledge / 4.2.11：
Lessons Learned
Appendix / 5：
The IRIS Data Set
References
Index
Introduction / 1：
What Is Data Mining? / 1.1：
Some More Real-World Applications / 1.2：
5.

図書
図書
5. Medical data analysis : 4th International Symposium, ISMDA 2003, Berlin, Germany, October 9-10, 2003 : proceedings
Petra Perner, Rüdiger Brause, Hermann-Georg Holzhütter (eds.)
出版情報: Berlin ; Tokyo : Springer, c2003  viii, 126 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2868
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6.

図書
図書
6. Machine learning and data mining in pattern recognition : second International Workshop, MLDM 2001, Leipzig, Germany, July 25-27, 2001 : proceedings
Petra Perner (ed.)
出版情報: Berlin ; Tokyo : Springer, c2001  xi, 361 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2123 . Lecture notes in artificial intelligence
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目次情報: 続きを見る
Invited Paper
Technology of Text Mining / A. Visa
Evaluation of Clinical Relevance of Clinical Laboratory Investigations by Data Mining / U. Sack ; M. Kamprad
Case-Based Reasoning and Associative Memory
Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications / R. Schmidt ; L. Gierl
Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin? / P. Perner
FAM-Based Fuzzy Inference for Detecting Shot Transitions / S.-W. Jang ; G.-Y. Kim ; H.-I. Choi
Rule Induction and Grammars
Rule-Based Ensemble Solutions for Regression / N. Indurkhya ; S. M. Weiss
Learning XML Grammars / H. Fernau
First-Order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps / D. Malerba ; F. Esposito ; A. Lanza ; F.A. Lisi
Clustering and Conceptual Clustering
Concepts Learning with Fuzzy Clustering and Relevance Feedback / B. Bhanu ; A. Dong
LC: A Conceptual Clustering Algorithm / J. F. Martinez-Trinidad ; G. Sanchez-Diaz
Data Mining on Signal, Images, Text and Temporal-Spatial Data
Data Mining Approach Based on Information-Statistical Analysis: Application to Temporal-Spatial Data / B.K. Sy ; A.K. Gupta
A Hybrid Tool for Data Mining in Picture Archiving System / T. Belikova
Feature Selection for a Real-World Learning Task / D. Kollmar ; D.H. Hellmann
Automatic Identification of Diatoms Using Decision Forests / S. Fischer ; H. Bunke
Validation of Text Clustering Based on Document Contents / J. Toivonen ; A.Visa ; T. Vesanen ; B. Back ; H. Vanharanta
Nonlinear Function Learning and Neural Net Based Learning
Statistical and Neural Approaches for Estimating Parameters of a Speckle Model Based on the Nakagami Distribution / M.P. Wachowiak ; R. Smolíkova ; M.G. Milanova ; A.S. Elmaghraby
How to Automate Neural Net Based Learning / R. Linder ; S.J. Poppl
Nonlinear Function Learning and Classification Using Optimal Radial Basis Function Networks / A. Krzy&Zdot above;ak
Learning for Handwriting Recognition
Local Learning Framework for Recognition of Lowercase Handwritten Characters / J.-x. Dong ; C.Y. Suen
Mirror Image Learning for Handwritten Numeral Recognition / M. Shi ; T. Wakabayashi ; W. Ohyama ; F. Kimura
Statistical and Evolutionary Learning
Face Detection by Aggregated Bayesian Network Classifiers / T.V. Pham ; M. Worring ; A.W.M. Smeulders
Towards Self-Exploring Discriminating Features / Y. Wu ; T.S. Huang
PCA-Based Model Selection and Fitting for Linear Manifolds / A. Imiya ; H. Ootani
Statistics of Flow Vectors and Its Application to the Voting Method for the Detection of Flow Fields / K. Iwawaki
On the Use of Pairwise Comparison of Hypotheses in Evolutionary Learning Applied to Learning from Visual Examples / K. Krawiec
Featureless Pattern Recognition in an Imaginary Hilbert Space and Its Application to Protein Fold Classification / V. Mottl ; S. Dvoenko ; O. Seredin ; C. Kulikowski ; I. Muchnik
Content-Based Image Retrieval
Adaptive Query Shifting for Content-Based Image Retrieval / G. Giacinto ; F. Roli ; G. Fumera
Content-Based Similarity Assessment in Multi-segmented Medical Image Data Bases / G. Potamias
Author Index
Invited Paper
Technology of Text Mining / A. Visa
Evaluation of Clinical Relevance of Clinical Laboratory Investigations by Data Mining / U. Sack ; M. Kamprad
7.

図書
図書
7. Advances in data mining : applications in E-commerce, medicine, and knowledge management
Petra Perner (ed.)
出版情報: Berlin : Springer, c2002  107 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2394 . Lecture notes in artificial intelligence
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Data Mining and E-commerce
Sequence Rules for Web Clickstream Analysis / Erika Blanc ; Paolo Giudici
Data Mining of Association Rules and the Process of Knowledge Discovery in Databases / Jochen Hipp ; Ulrich Güntzer ; Gholamreza Nakhaeizadeh
Intelligent E-marketing with Web Mining, Personalization, and User-Adpated Interfaces / Petra Perner ; G. Fiss
Knowledge Management and Data Mining
The indiGo Project: Enhancement of Experience Management and Process Learning with Moderated Discourses / Klaus-Dieter Althoff ; Ulrike Becker-Kornstaedt ; Björn Decker ; Andreas Klotz ; Edda Leopold ; Jorg Rech ; Angi Voss
Medical Applications
Genomic Data Explosion - The Challenge for Bioinformatics? / Anne Glass ; Thomas Karopka
Case-Based Reasoning for Prognosis of Threatening Influenza Waves / Rainer Schmidt ; Lothar Gierl
Author Index
Data Mining and E-commerce
Sequence Rules for Web Clickstream Analysis / Erika Blanc ; Paolo Giudici
Data Mining of Association Rules and the Process of Knowledge Discovery in Databases / Jochen Hipp ; Ulrich Güntzer ; Gholamreza Nakhaeizadeh
8.

図書
図書
8. Pattern recognition and image analysis : Third International Conference on Advances in Pattern Recognition, ICAPR 2005 Bath, UK, August 22-25, 2005 : proceedings, part II
Sameer Singh ... [et al.] (eds.)
出版情報: Berlin : Springer, c2005  xxv, 809 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 3687
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9.

図書
図書
9. Advances in data mining : applications in medicine, web mining, marketing, image and signal mining : 6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 14-15, 2006 : proceedings
Petra Perner (eds.)
出版情報: Berlin : Springer, c2006  xi, 592 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 4065 . Lecture notes in artificial intelligence
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10.

図書
図書
10. Machine learning and data mining in pattern recognition : 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005 : proceedings
Petra Perner, Atsushi Imiya (eds.)
出版情報: Berlin : Springer, c2005  xvii, 695 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 3587 . Lecture notes in artificial intelligence
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