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ORCID2. IDA 1997: London, UK
- Xiaohui Liu, Paul R. Cohen, Michael R. Berthold:
Advances in Intelligent Data Analysis, Reasoning about Data, Second International Symposium, IDA-97, London, UK, August 4-6, 1997, Proceedings. Lecture Notes in Computer Science 1280, Springer 1997, ISBN 3-540-63346-4 - David J. Hand:
Intelligent Data Analysis: Issues and Opportunities. 1-14
Section I: Exploratory Data Analysis, Preprocessing, and Tools
- Chidanand Apté, Se June Hong, Jonathan R. M. Hosking, Jorge Lepre, Edwin P. D. Pednault, Barry K. Rosen:
Decomposition of Heterogeneous Classification Problems. 17-28 - Michael William Muller:
Managing Dialogue in a Statistical Expert Assistant with a Cluster-Based User Model. 29-40 - Catherine C. McGeoch, Doina Precup, Paul R. Cohen:
How to Find Big-Oh in Your Data Set (and How Not to). 41-52 - Ian Berry, Michael Paul Gough:
Data Classification using a W.I.S.E. Toolbox. 53-64 - Tremaine A. O. Cornish:
Mill's Methods for Complete Intelligent Data Analysis. 65-76 - Dawn E. Gregory, Paul R. Cohen:
Integrating Many Techniques for Discovering Structure in Data. 77-88 - Robert Levinson, Jeff Wilkinson:
Meta-Reasoning for Data Analysis Tool Allocation. 89-100 - Robert St. Amant:
Navigation for Data Analysis Systems. 101-109 - Christine L. Tsien, James C. Fackler:
An Annotated Data Collection System to Support Intelligent Analysis of Intensive Care Unit Data. 111-121 - Hairong Yu, Arthur Ramer:
A Combined Approach to Uncertain Data Analysis. 123-134
Section II: Classification and Feature Selection
- Kristina Schädler, Fritz Wysotzki:
A Connectionist Approach to the Distance-Based Analysis of Relational Data. 137-148 - Robin P. Glover, Peter K. Sharpe:
Efficient GA Based Techniques for Automating the Design of Classification Models. 149-160 - Chiou Peng Lam, Geoff A. W. West, Terry Caelli:
Data Representations and Machine Learning Techniques. 161-172 - Suzanne Lo, Fazel Famili:
Development of a Knowledge-Driven Constructive Induction Mechanism. 173-185 - João Gama
:
Oblique Linear Tree. 187-198 - S. Haring, Joost N. Kok, Michiel C. van Wezel:
Feature Selection for Neural Networks through Functional Links Found by Evolutionary Computation. 199-210 - David D. Jensen, Tim Oates, Paul R. Cohen:
Building Simple Models: A Case Study with Decision Trees. 211-222 - Massimo Piccardi, Rita Cucchiara, Michele Bariani, Paola Mello:
Exploiting Symbolic Learning in Visual Inspection. 223-234 - Paul D. Scott, R. J. Williams, K. M. Ho:
Forming Categories in Exploratory Data Analysis and Data Mining. 235-246 - Maarten van Someren, Cristina Torres, Floor Verdenius:
A Systematic Description of Greedy Optimisation Algorithms for Cost Sensitive Generalisation. 247-257 - Petko Valtchev, Jérôme Euzenat:
Dissimilarity Measure for Collections of Objects and Values. 259-272
Section III: Medical Applications
- H. J. L. M. Vullings, M. H. G. Verhaegen, Henk B. Verbruggen:
ECG Segmentation Using Time-Warping. 275-285 - Riccardo Bellazzi, Cristiana Larizza, Alberto Riva:
Interpreting Longitudinal Data through Temporal Abstractions: An Application to Diabetic Patients Monitoring. 287-298 - Vera Kamp, Frank Wietek:
Intelligent Support for Multidimensional Data Analysis in Environmental Epidemiology. 299-310
Section IV: Soft Computing
- Steve R. Gunn, Martin Brown, Kev M. Bossley:
Network Performance Assessment for Neurofuzzy Data Modelling. 313-323 - Susana Nascimento, Fernando Moura-Pires:
A Genetic Approach to Fuzzy Clustering with a Validity Measure Fitness Function. 325-335 - Chris M. Roadknight, Dominic Palmer-Brown, Gina E. Mills:
The Analysis of Artificial Neural Network Data Models. 337-346 - Klaus-Peter Huber, Michael R. Berthold:
Simulation Data Analysis Using Fuzzy Graphs. 347-358 - Frank Klawonn, Erich-Peter Klement:
Mathematical Analysis of Fuzzy Classifiers. 359-370 - Andreas Lapp, H.-G. Kranz:
Neuro-Fuzzy Diagnosis System with a Rated Diagnosis Reliability and Visual Data Analysis. 371-382 - Meltem Turhan:
Genetic Fuzzy Clustering by Means of Discovering Membership Functions. 383-393
Section V: Knowledge Discovery and Data Mining
- David McSherry:
A Strategy for Increasing the Efficiency of Rule Discovery in Data Mining. 397-408 - Klemens Schnattinger, Udo Hahn:
Intelligent Text Analysis for Dynamically Maintaining and Updating Domain Knowledge Bases. 409-422 - Michael Schlosser:
Knowledge Discovery in Endgame Databases. 423-435 - John Darlington, Yike Guo, Janjao Sutiwaraphun, Hing Wing To:
Parallel Induction Algorithms for Data Mining. 437-445 - Jerome Robinson, Barry G. T. Lowden:
Data Analysis for Query Processing. 447-458 - Laurent Siklóssy, Marc Ayel:
Datum Discovery. 459-463 - Yuanhui Zhou, Yuchang Lu, Chunyi Shi:
A Connectionist Approach to Extracting Knowledge from Databases. 465-475
Section VI: Estimation, Clustering
- G. C. van den Eijkel, Jan C. A. van der Lubbe, Eric Backer:
A Modulated Parzen-Windows Approach for Probability Density Estimation. 479-489 - María del Mar Rueda García, Antonio Arcos Cebrián, E. Artés Rodríguez:
Improvement on Estimating Quantiles in Finite Population Using Indirect Methods of Estimation. 491-499 - Yurij S. Kharin:
Robustness of Clustering under Outliers. 501-511 - Erich Schikuta, Martin Erhart:
The BANG-Clustering System: Grid-Based Data Analysis. 513-524
Section VII: Data Quality
- Wei Zhong Liu, Allan P. White, Simon G. Thompson, Max A. Bramer:
Techniques for Dealing with Missing Values in Classification. 527-536 - Marco Ramoni, Paola Sebastiani:
The Use of Exogenous Knowledge to Learn Bayesian Networks from Incomplete Databases. 537-548 - John Xingwang Wu, Gongxian Cheng, Xiaohui Liu:
Reasoning about Outliers by Modelling Noisy Data. 549-558
Section VIII: Qualitative Models
- Elizabeth Bradley, Matthew Easley:
Reasoning about Sensor Data for Automated System Identification. 561-572 - Adele E. Howe, Gabriel Somlo:
Modelling Discrete Event Sequences as State Transition Diagrams. 573-584 - Sarah Boyd:
Detecting and Describing Patterns in Time-Varying Data Using Wavelets. 585-596 - Björn Schieffer, Günter Hotz:
Diagnosis of Tank Ballast Systems. 597-608 - Olaf Wolkenhauer:
Qualitative Uncertainty Models from Random Set Theory. 609-620
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