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Bootstrapping Domain Ontologies from Wikipedia: A Uniform Approach

AAAI Conferences

Building ontologies is a difficult task requiring skills in logics and ontological analysis. Domain experts usually reach as far as organizing a set of concepts into a hierarchy in which the semantics of the relations is under-specified. The categorization of Wikipedia is a huge concept hierarchy of this form, covering a broad range of areas. We propose an automatic method for bootstrapping domain ontologies from the categories of Wikipedia. The method first selects a subset of concepts that are relevant for a given domain. The relevant concepts are subsequently split into classes and individuals, and, finally, the relations between the concepts are classified into subclass_of, instance_of, part_of, and generic related_to. We evaluate our method by generating ontology skeletons for the domains of Computing and Music. The quality of the generated ontologies has been measured against manually built ground truth datasets of several hundred nodes.


Coping with Changing Ontologies in a Distributed Environment

AAAI Conferences

We discuss the problems associated with versioning ontologies in distributed environments. This is an important issue because ontologies can be of great use in structuring and querying intemet information, but many of the Intemet's characteristics, such as distributed ownership, rapid evolution, and heterogeneity, make ontology management difficult. We present SHOE, a web-based knowledge representation language that supports multiple versions of ontologies. We then discuss the features of SHOE that address ontology versioning, the affects of ontology revision on SHOE web pages, and methods for implementing ontology integration using SHOE's extension and version mechanisms. 1. Introduction As the use of ontologies becomes more prevalent, there is a more pressing need for good ontology management schemes. This is especially true once an ontology has been used to structure data, since changing it can be very expensive. Often the solution is to "get it right the first time", however, in long term applications, there is always the chance that new information will be discovered or that different features of the domain will become important. Therefore, we must think of ontology development as an ongoing process. In a centralized environment, it may be possible to coordinate ontology revisions with corresponding revisions to the data that was structured using the ontology. However, as the volume of data increases this become more difficult.


What Is Ontology Merging?

AAAI Conferences

In this paper we explain how merging of ontologies is captured by the pushout construction from category theory, and argue that this is a very natural approach to the problem. We study this independent of a specific choice of ontology representation language, and thus provide a sort of blueprint for the development of algorithms applicable in practice. For this purpose, we view category theory as a universal "meta specification language" that enables us to specify properties of ontological relationships and constructions in a way that does not depend on any particular implementation. This can be achieved since the basic objects of study in category theory are the relationships between multiple ontological specifications, not the internal structure of a single knowledge representation. Categorical pushouts are already considered in some approaches to ontology research (Jannink et al. 1998; Schorlemmer, Potter, & Robertson 2002; Goguen 2005; Kent 2005) and we do not claim our treatment to be entirely original.


Ontological Engineering with Principled Core Ontologies

AAAI Conferences

For instance, the category "disease" refers to knowledge about diseases, which may include a taxonomy of "diseases" (where disease is now used as a term).


Representing Interaction Protocols in DAML

AAAI Conferences

We present an extension to DAML-S for representing interaction protocols. An interaction protocol defines the messaging patterns between communicating entities such as software agents. Serializing interaction protocols in a suitable form for reuse supports creating software agents capable of adapting to various environments. Serialized interaction protocols can be utilized, for example, when specifying details of interaction between a contractor and a subcontractor operating in the Internet.