Mapping part-whole hierarchies into connectionist networks
Artificial Intelligence - On connectionist symbol processing
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
The object data standard: ODMG 3.0
The object data standard: ODMG 3.0
Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential
Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential
Prolog/Rex-A Way to Extend Prolog for Better Knowledge Representation
IEEE Transactions on Knowledge and Data Engineering
DAML+OIL: An Ontology Language for the Semantic Web
IEEE Intelligent Systems
Database in Depth: Relational Theory for Practitioners
Database in Depth: Relational Theory for Practitioners
Knowledge representation with SOUL
Expert Systems with Applications: An International Journal
FAQ-master: an ontological multi-agent system for web FAQ services
WSEAS Transactions on Information Science and Applications
Applying neural networks to knowledge representation and determination of its meaning
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Developing a question answering system for the slovene language
WSEAS Transactions on Information Science and Applications
A semantic schema - based approach for natural language translation
WSEAS Transactions on Computers
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The processing of semantic information requires the adequate knowledge representation and ability to interpret semantically related knowledge. The majority of present day approaches to knowledge representation and processing are based on symbolic approach, i.e. on describing the meaning of represented domain knowledge and procedural knowledge used to process this domain knowledge. Hierarchical Semantic Form (HSF) implements the semantic approach to semantic knowledge representation and processing, which is not based on naming as a means to describe the meaning of the knowledge, but on semantic contexts that enable an implicit way to define the meaning of represented knowledge, and on simple and complex semantic categories used to interpret the semantics of represented knowledge. HSF facilitates the automatic translation of knowledge expressed in natural language into structured form and vice versa with no loss of information and its processing including natural language understanding, semantic search and question answering.