KEOD 2012 - International Conference on Knowledge Engineering and Ontology Development

Knowledge Engineering (KE) refers to all technical, scientific and social as-pects involved in building, maintaining and using knowledge-based systems. KE is a multidisciplinary field, bringing in concepts and methods from several computer science domains such as artificial intelligence, databases, expert systems, decision support systems and geographic information systems. From the software development point of view, KE uses principles that are strongly related to software engineering. KE is also related to mathematical logic, as well as strongly involved in cognitive science and socio-cognitive engineering where the knowledge is produced by humans and is structured according to our understanding of how human reasoning and logic works. Currently, KE is gradually more related to the construction of shared conceptual frameworks, often designated as ontologies.
Ontology Development (OD) aims at building reusable semantic structures that can be informal vocabularies, catalogs, glossaries as well as more complex finite formal structures representing the entities within a domain and the relationships between those entities. Ontologies, have been gaining interest and acceptance in computational audiences: formal ontologies are a form of software, thus software development methodologies can be adapted to serve ontology development. A wide range of applications is emerging, especially given the current web emphasis, including library science, ontology-enhanced search, e-commerce and business process design.
KEOD aims at becoming a major meeting point for researchers and practitioners interested in the study and development of methodologies and technologies for Knowledge Engineering and Ontology Development.
CONFERENCE TOPICS
Knowledge Representation
Knowledge Acquisition
Context Analysis and Modeling
Decision Support Systems
Expert Systems
Ontology Engineering
Semantic Web
Process knowledge and semantic services
Ontology sharing and reuse
Ontology matching and alignment
Knowledge reengineering
AI programming
Intelligent Problem Solving
Natural language processing
Human-Machine Cooperation
Information Integration
Applications and case-studies
Domain Analysis and Modeling
Metamodelling
Education and Training Issues
Enterprise Ontology