Machine learning and data mining in pattern recognition(模式识别中的机器学习与数据开采)

The LNAI series reports state-of-the-art results in artificial intelligence re-search，development，and education，at a high level and in both printed and electronic form. Enjoying tight cooperation with the R＆D community，with numerous individuals，as well as with prestigious organizations and societies，LNAI has grown into the most comprehensive artificial intelligence research forum available.
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proceedings（published in time for the respective conference）
post-proceedings（consisting of thoroughly revised final full papers）
research monographs（which may be based on PhD work）

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This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition, MLDM 2001, held in Leipzig, Germany in July 2001.
The 26 revised full papers presented together with two invited papers were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections on case-based reasoning and associative memory; rule induction and grammars; clustering and conceptual clustering; data mining on signals, images, and spatio-temporal data; nonlinear function learning and neural net based learning; learning for handwriting recognition; statistical and evolutionary learning; and content-based image retrieval.

Invited Paper
Technology of Text Mining
Evaluation of Clinical Relevance of Clinical Laboratory Investigations by Data Mining
Case-Based Reasoning and Associative Memory
Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications
Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin?
FAM-Based Fuzzy Inference for Detecting Shot Transitions
Rule Induction and Grammars
Rule-Based Ensemble Solutions for Regression
Learning XML Grammars
First-Order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps
Clustering and Conceptual Clustering
Concepts Learning with Fuzzy Clustering and Relevance Feedback
LC: A Conceptual Clustering Algorithm
Data Mining on Signal, Images, Text and Temporal-Spatial Data
Data Mining Approach Based on Information-Statistical Analysis Application to Temporal-Spatial Data
A Hybrid Tool for Data Mining in Picture Archiving System
Feature Selection for a Real-World Learning Task
Automatic Identification of Diatoms Using Decision Forests
Validation of Text Clustering Based on Document Contents
Nonlinear Function Learning and Neural Net Based Learning
Statistical and Neural Approaches for Estimating Parameters of a Speckle Model Based on the Nakagami Distribution
How to Automate Neural Net Based Learning
Nonlinear Function Learning and Classification Using Optimal Radial Basis Function Networks
Learning for Handwriting Recognition
Local Learning Framework for Recognition of Lowercase Handwritten Characters
Mirror Image Learning for Handwritten Numeral Recognition
Statistical and Evolutionary Learning
Face Detection by Aggregated Bayesian Network Classifiers
Towards Self-Exploring Discriminating Features
……
Content-Based Image Retrieval
Author Index