Predicting the Future: AI Approaches to Time-Series Problems: Papers from the 1998 AAAI Workshop
Contents
An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback
PDFA General Paradigm for Applying Machine Learning in Automated Manufacturing Processes
PDFLearning to Predict Rare Events in Categorical Time-Series Data
PDFPattern Discovery in Temporal Databases: Some Recent Results
PDFDiscovering Rules for Clustering and Predicting Asynchronous Events
PDFPredicting Resource Usages with Incomplete Information
PDFApproaches to Online Learning and Concept Drift for User Identification in Computer Security
PDFFiltering Techniques for Rapid User Classification
PDFA Probabilistic Approach to Fast Pattern Matching in Time Series Databases
PDFPreface
PDFA New Mixture Model for Concept Learning from Time Series
PDFHeterogeneous Time Series Learning for Crisis Monitoring
PDFLearning in Time Ordered Domains with Hidden Changes in Context
PDFEarly Prediction of Electric Power System Blackouts by Temporal Machine Learning
PDFAutomated Design of User Profiling Systems for Fraud Detection
PDFPredicting Sequences of User Actions
PDFModeling Periodic Functions for Time Series Analysis
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