Temporal Data Mining, Simultaneous Multi-sequence,
Relation Temporal logic, Spatial and Temporal Data.

  

  【Research Progress】

   
Viterbi
Zadeh
 

數據採掘 Data Mining

Cyber Home School

    eLearning Platform

    Platform Layout

    Tracking Techniques

MetaCode

    Meta  

    Metacode

    

Papers

    Wang, Wei

    James F. Allen

    Eamonn Keogh
 
Thesis

Algorithm

 Mörchen Time Series Knowledge Mining

Shannon Theory

Mooney Interacting Episodes & Temporal Rule

Huffman Code

 Höppner Knowledge Discovery (sequential data)

Viterbi Algorithm

 Papapatrou Constraint-based -- Temporal Intervals    
 Zhao Algorithms for Multiple Streaming Time

Cause & Effect

 Hetland Evolving Sequence Rules

Entropy

Vilo Pattern Discovery from Biosequences    
Brito Causal Graphical Methods    
 
Journal

Notes

Paper's References 1  2  3  4  

Pattern Mining

SPAN 1  2  3  4  5  6

Spatio-Temporal Query

Decision Making System 1 

Entropy

Frequent Matching 1  2  3  4  5

PrefixSpan

Association Rule 1  2  

Sequential Mining

Time-series 1  2  3  4  5
Subsequence 1  2  3  4

Frequent Matching

Mining Patterns 1  2  3  4  5  6  

Common Cause

Probabilistic Sequence 1  2  3 
Granulation 1  2  3  4 
 
Papers
Discovering Frequent Poly-Regions in DNA Sequences
Maintaining Knowledge about Temporal Intervals
Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences
Discovery of Frequent Episodes in Event Sequences
Composition Alignment
Discovering Frequent Arrangements of Temporal Intervals
Unsupervised Pattern Mining from Symbolic Temporal Data

Learning Sequential Patterns for Probabilistic Inductive Prediction
Symbolic Used-Defined Periodicity in Temporal Relational Databases
Temporal Reasoning Based on Semi-Intervals
Meta-Rule-Guided Mining of Association Rules in Relational Databases
Domain-Driven Actionable Knowledge Discovery in the Real World
Temporal Aggregation and Spurious Instantaneous Causality in Multiple Time Series Models
Online Event-driven Subsequence Matching over Financial Data Streams
Mining Sequential Patterns
Clustering over Multiple Evolving Streams by Events and Correlations
Stock Time Series Pattern Matching: Template-based vs. Rule-based approaches
Meta-Rule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes
Finding Interesting Rules from Large Sets of Discovered Association Rules
An algorithm for discovering richer relative temporal association rules from interval-based data
Multi-dimensional Sequential Pattern Mining
Streaming Pattern Discovery in Multiple Time-Series
Distributed Pattern Discovery in Multiple Streams
Data Mining of Multiple Non-stationary Time Series
Discovering Sequential Association Rules with Constraints and Time Lags in Multiple Sequences
Discovering Similar Patterns in Time Series
A symbolic representation of time series, with implications for streaming algorithms
Probabilistic Discovery of Time Series Motifs
Mining Frequent Episodes for Relating Financial Events and Stock Trends
Indexing Multi-Dimensional Time-Series with Support for Multiple Distance Measures
Mining Hierarchical Temporal Patterns in Multivariate Time Series
 
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 K. C. Kao 與 G. A. Hockham 於1966年發表應用玻璃纖維作為傳輸介質的原始論文
Dielectric-Fibre Surface Waveguides For Optical frequencies
這項研究首先提出使用玻璃纖維來實現光通信，是現今光纖通信的基礎。