Advances in Intelligent Data Analysis. Reasoning about Data Second International Symposium, IDA-97, London, UK, August 4-6, 1997, Proceedings /

This book constitutes the refereed proceedings of the Second International Symposium on Intelligent Data Analysis, IDA-97, held in London, UK, in August 1997. The volume presents 50 revised full papers selected from a total of 107 submissions. Also included is a keynote, Intelligent Data Analysis: I...

Full description

Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Liu, Xiaohui (Editor, http://id.loc.gov/vocabulary/relators/edt), Cohen, Paul (Editor, http://id.loc.gov/vocabulary/relators/edt), Berthold, Michael R. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1997.
Edition:1st ed. 1997.
Series:Lecture Notes in Computer Science, 1280
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Intelligent data analysis: Issues and opportunities
  • Decomposition of heterogeneous classification problems
  • Managing dialogue in a statistical expert assistant with a cluster-based user model
  • How to find big-oh in your data set (and how not to)
  • Data classification using a W.I.S.E. toolbox
  • Mill's methods for complete Intelligent Data Analysis
  • Integrating many techniques for discovering structure in data
  • Meta-Reasoning for Data Analysis Tool Allocation
  • Navigation for data analysis systems
  • An annotated data collection system to support intelligent analysis of Intensive Care Unit data
  • A combined approach to uncertain data analysis
  • A connectionist approach to the distance-based analysis of relational data
  • Efficient GA based techniques for automating the design of classification models
  • Data representations and machine learning techniques
  • Development of a knowledge-driven constructive induction mechanism
  • Oblique linear tree
  • Feature selection for neural networks through functional links found by evolutionary computation
  • Building simple models: A case study with decision trees
  • Exploiting symbolic learning in visual inspection
  • Forming categories in exploratory data analysis and data mining
  • A systematic description of greedy optimisation algorithms for cost sensitive generalisation
  • Dissimilarity measure for collections of objects and values
  • ECG segmentation using time-warping
  • Interpreting longitudinal data through temporal abstractions: An application to diabetic patients monitoring
  • Intelligent support for multidimensional data analysis in environmental epidemiology
  • Network performance assessment for Neurofuzzy data modelling
  • A genetic approach to fuzzy clustering with a validity measure fitness function
  • The analysis of artificial neural network data models
  • Simulation data analysis using Fuzzy Graphs
  • Mathematical analysis of fuzzy classifiers
  • Neuro-fuzzy diagnosis system with a rated diagnosis reliability and visual data analysis
  • Genetic Fuzzy Clustering by means of discovering membership functions
  • A strategy for increasing the efficiency of rule discovery in data mining
  • Intelligent text analysis for dynamically maintaining and updating domain knowledge bases
  • Knowledge discovery in endgame databases
  • Parallel induction algorithms for data mining
  • Data analysis for query processing
  • Datum discovery
  • A connectionist approach to extracting knowledge from databases
  • A modulated Parzen-windows approach for probability density estimation
  • Improvement on estimating quantites in finite population using indirect methods of estimation
  • Robustness of clustering under outliers
  • The BANG-clustering system: Grid-based data analysis
  • Techniques for dealing with missing values in classification
  • The use of exogenous knowledge to learn Bayesian Networks from incomplete databases
  • Reasoning about outliers by modelling noisy data
  • Reasoning about sensor data for automated system identification
  • Modelling discrete event sequences as state transition diagrams
  • Detecting and describing patterns in time-varying data using wavelets
  • Diagnosis of tank ballast systems
  • Qualitative uncertainty models from random set theory.