Structuring superconductor data with ontology: reproducing historical datasets as knowledge bases

Incremental structuring of knowledge bases

An important structuring mechanism for knowledge bases is building an inheritance hierarchy of classes based on the content of their knowledge objects. The hierarchy can be used to handle several query processing tasks more efficiently. Building and maintaining this hierarchy is a difficult task for the knowledge engineer. The notion of knowledge space has been previously proposed to help autom...

Ontology Extraction for Educational Knowledge Bases

A student who wishes to learn about some particular topic does not have many options. An often used tool is the search engine, which gives a tiny and difficult to control window into the vast amounts of information that is available on the Internet. A student who wants to learn some concept should be able to interact with the available information in a coherent and personalized way. The classro...

Automatic Structuring of Knowledge Bases by Conceptual Clustering

Uniformly Querying Knowledge Bases and Data Bases

Present kl-one-like knowledge base management systems (KBMS), whilst ooer-ing highly structured description languages aside eecient concepts classiication, have limited capability to manage large amounts of individuals. Data base management systems (DBMS) can, instead, manage large amounts of data eeciently, but give scarce formalism to organize them in a structured way, and to reason with them...

Contextual Diagrams as Structuring Mechanisms for Designing Configuration Knowledge Bases in UML

Lower prices, shorter product cycles, and the customer individual production of highly variant products are the main reasons for the success of product configuration systems in various application domains (telecommunication industry, automotive industry, computer industry). In this paper we show how to employ UML in order to design complex configuration knowledge bases. We introduce the notion ...