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Hewlett-Packard -- Synthesis of Ontologies Rapidly for Commercial Enterprise

Ontologies and the Semantic Web technologies

The Semantic Web (SW) is an extension of the World Wide Web which makes explicit the semantics or meaning of information and services. For a short and intuitive introduction to the difference between WWW and SW, see the following video or the following slides. For a slightly more extensive primer, see Tim berners Lee's Roadmap. Ontologies are a key component of the Semantic Web; from the slides linked above:

"The Semantic Web is a collection of standard technologies to realize a Web of Data. Of course, the devil is in the details - a common model has to be provided for machines to describe, query, etc, the data and their connections. The “classification” of the terms can become very complex for specific knowledge areas: this is where ontologies,  thesauri, etc, enter the game… "

HP are interested in Semantic Web technology in enterprise applications. In a corporate environment, these technologies offer the promise of effective re-use and retainment of corporate knowledge as well as leveraging of distributed, diverse knowledge resources through automated inference across a large company. The main benefit of the WWW and its open, standardized technologies (HTML, HTTP) is that it facilitates the unexpected re-use of web pages. The proposed benefit of the SW is that it will facilitate the unexpected re-use of data about the world. 

Ontology mapping and integration

Different departments, companies and organizations are likely want to create their own ontologies describing the particular aspects and recording those regularities of the world that they are interested in. There are two immidiate problems that need solving: (1) in order for data re-use to work, these disparate models (ontologies) of the world need to be reconciled (2) we ideally want to be able to construct ontologies and the relationships between them quickly and cheaply using automated methods.

Ontology mapping is the art of automatically finding relationships between ontologies. Ontology learning is the art of writing programs to automatically generate ontologies from extant non-semantic resources, for example from plain text.

Theoretical methods for ontology integration

The aim of this project is to investigate theoretical methods which might shed light on this situation. A variety of theories such as information flow theory, contextual and nonmonotonic logic, chu space theory and Dana Scott's information systems are being investigated to give a theoretical foundation and a mathematical theory governing the reconciliation of different viewpoints on the world and different models. We are also looking at example systems to test and evaluate these theoretical methods, including the CYC commonsense reasoning project and approximate theories of Conway's Game of Life.

Our project will provide an extended literature survey covering these theoretical methods, and a set of examples illustrating what they can do.


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