Knowledge Management (and Data Mining)

Objective:


Introduce the student in the world of knowledge management, the methodologies, the techniques and the tools to capture, to validate and to use knowledge. Among these techniques, we will put special attention in some ones coming from the area of Data Mining. These are useful to take conclusions from the intelligent analysis of the data and, therefore, as a support to decision making.

Contents:
1.- Introduction to Knowledge Management
    1.1 Description and Objectives
    1.2 Knowledge Management Model
    1.3 Data, Information, Knowledge, etc.
    1.4 Sorts of Knowledge and Representations
    1.5 Knowledge Engineering

2.- Technologies from a Historical Prespective
    2.1 A Brief History of Computer-Based Knowledge Management
    2.2 First Generation Knowledge Management
    2.3 Second Generation Knowledge Management

3.- Knowledge Representation Standards
    3.1 Ontologies
    3.2 Introduction to CommonKADS
    3.3 Introduction to Protégé
    3.4 Other tools
    3.5 Knowledge in the Web: HTML, XML, RDF, OWL
    3.6 Semantic Web

4.- Techniques and tools for Knowledge Management   
    4.1 Scope of the Techniques and Tools
    4.2 Information Retrieval Techniques and Tools
    4.3 Artificial Intelligence Techniques and Tools
    4.4 Other Techniques and Tools
       
5.- Introduction to Data Mining
    5.1 Data mining in KDD and in Knowledge Management
    5.2 Modeling Structures
    5.3 Algorithms for Data Mining
    5.4 Validation processes
    5.5 Data Mining tools
Material: