Part 2

Part 3

Part 4

Chapter 1.        History of Studies in Semantics from Information System perspective

·        With historical notes on semantics in other fields

·        Relevant views by Meersman, Weiderhold, etc.

Chapter 2.  Ontology for semantic underpinning in Information Systems

2.1              Historical notes about origins in philosophy to recent definitions by Gruber and Gurino;  covering ontologies, conceptual modeling, knowledge representation

·        Ontology, Knowledge Base, Conceptual Schema

2.2              Systems for knowledge organization: Dictionary, Taxonomy/Classification, Ontology, etc.

2.3              Ontology representation: expressiveness vs computability; representation choices: RDF(S), OWL, DAML+OIL, SUO borrowing from classifications by Mcllaraith,  Finin, etc.

2.4              Types and purpose of ontology: Dimension 1 (Gruber)

2.4.1        Formal: supports inferencing, unification

2.4.2        Semi-formal: supports matching and similarity/equality computations

2.4.3        Informal: Machine readable, but human interpretable (e.g., semantics of indentation, but not subsumption)

2.5              Types of ontology: Dimension 2

2.5.1        Upper ontology (time, space, etc)

2.5.2        General purpose ontologies (Cyc, CIRCA, WordNet, Cyc, UMLS medical ontology, EDR)

2.5.3        Domain ontologies

2.5.4        Application & Task ontologies

2.6              Ontology creation and management

2.6.1        Social process; human definition:

2.6.1.1  Tools for manual (e.g., OntoEdit, Protégé) and semi-automatic ontology creation (e.g., S-CREAM)

2.6.2        Creating ontologies from unstructured text corpus

2.6.2.1  Named entity extraction, relationship extraction

2.6.2.2  Ontology definition extraction (e.g., Ontominer)

2.6.3        Human definition of ontology and subsequent automatically knowledge extractions from trusted knowledge source (e.g., Semagix’s approach)

2.7              Tools for ontology creation, import, export, maintenance, lifecycle (brief)

2.8              Literature Overview

Chapter 3.        Fundamental Issues in semantics

3.1              Entity Disambiguation and Matching

3.2              Mismatch

3.3              Integration

3.3.1    Ontology mismatch and integration

3.3.2        Distinction between schema integration and ontology integration

3.4      Multi-ontology systems

3.5      Comprehensive literature overview 

Chapter 4.        Automatic Classification

                        Overview of research and techniques for automatic classification

                        Statistical, Machine Learning, Language Based and Knowledge Based techniques

                        Classifier committee

Chapter 5.        Semantic Metadata and Information Annotation

                        Sheth, Fischer

5.1      Metadata classification: from Syntax to Semantics

5.2      Metadata representation and choices for annotation

5.3      Extracting metadata from semi-structured data – including research,      techniques and tools

5.4     Extracting metadata from unstructured text– including research, techniques and tools

5.5    Comprehensive literature review

Chapter 6.        Relationships at the heart of semantics

                        Arpinar, Sheth, ??

·        Identification, Representation, Discovery, and Validation of

complex relations

·        Comprehensive literature review

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