Algorithmic and Combinatorial Foundations of Pattern Discovery

Posted in Science on October 28, 2008


Algorithmic and Combinatorial Foundations of Pattern Discovery

Lecture slides:

  • Monotony and Surprise Algorithmic and Combinatorial Foundations of Pattern Discovery
  • http://www.cc.gatech.edu/~axa/papers A) Speciali
  • http://www.cc.gatech.edu/~axa/papers B) Introductory Material
  • Acknowledgements Gill Bejerano
  • Form \x3D Function
  • TITLE
  • Bioinformatics the Road Ahead
  • At a joint EU \x2D US panel meeting
  • Which Information Anyway
  • King Phillip Came Over For Green Soup
  • The “Chinese” Taxonomy
  • Summary
  • Defining ‘’Class’’
  • Class by Intension
  • Statistical Classification
  • Statistical Classification
  • Statistical Classification
  • Inferring Grammars
  • Regular, Anomalous, Entropy, Negentropy
  • Random, Regular, Compressible
  • Random, Regular, Compressible
  • Form \x3D Function
  • Summary
  • Privileging Syntactic Regularities in Strings
  • Unavoidable Regularities
  • Avoidable Regularities
  • Periods cannot coexist too long
  • Avoidable Regularities
  • Squares or Tandem Repeats
  • Detecting Squares
  • Tandem Repeats, Repeated Episodes
  • Pattern Discovery in WAKA
  • Discovering instances of poetic allusion from anthologies of classical Japanese poems
  • Cheating by Schoolteachers (the longest substring common to k of n strings)
  • Summary
  • General Form of Pattern Discovery
  • Data Compression by Textual Substitution
  • Consumer Prediction (Data Mining) Intrusion Detection (Security) Protein Classification (Bio\x2DInformatics)
  • Of Exactitude in Science

Author: Alberto Apostolico, University Of Padova

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