Embedding knowledge in Web documents
The paper argues for the use of general and intuitive knowledge representation languages (and simpler notational variants, e.g. subsets of natural languages) for indexing the content of Web documents and representing knowledge within them. We believe that these languages have advantages over metadata languages based on the Extensible Mark-up Language (XML). Indeed, the retrieval of precise information is better supported by languages designed to represent semantic content and support logical inference, and the readability of such a language eases its exploitation, presentation and direct insertion within a document (thus also avoiding information duplication). We advocate the use of Conceptual Graphs and simpler notational variants that enhance knowledge readability. To further ease the representation process, we propose techniques allowing users to leave some knowledge terms undeclared. We also show how lexical, structural and knowledge-based techniques may be combined to retrieve or generate knowledge or Web documents. To support and guide the knowledge modeling approach, we present a top-level ontology of 400 concept and relation types. We have implemented these features in a Web-accessible tool named WebKB2, and show examples to illustrate them.
knowledge modeling ontology precision-oriented information retrieval knowledge-based indexation and annotation data and metadata management