1. Data manipulation techniques for adaptation Alexandra I. Cristea USI intensive course “Adaptive Systems” April-May 2003

2. Overview: Data manipulation 1.Data manipulation: what is it? 2.Subsymbolic vs. symbolic techniques

3. Data manipulation Data manipulation means using the data For a given data representation, many possible data manipulations (& techniques) are possible

4. Objectives of data manipulation Views on the data –(e.g., in ITS, AH for learning) Data analysis Data verification Data filtering Etc.

5. Symbolic data manipulation

6. Data manipulation mechanisms Propositional logic, predicate logic and production systems facilitate dealing with symbolic systems Data manipulation language: –Examples: SQL, rule-language, (relational) algebras, production languages, logic programming

7. Adaptive Hypermedia data manipulation Adaptation module (AM): –IF-THEN rules (or CA rules) Adaptation engine (AE): –Applying AM

8. Subsymbolic data manipulation

9. Subsymbolic data manipulation mechanisms NN learning algorithms Clustering techniques GA Fuzzy logics computation Etc.