Is It Worth a Hoot? Qualms about OWL for Uncertainty Reasoning
Mike Pool1, Francis Fung2, Stephen Cannon1, Jeffrey Aikin1
赫赫，我这外行看此文感觉很舒服，结尾涉及了owl是否适合作为sw reasoning的分析，觉得不错。如有不妥让各位见笑请担待则个
结尾〉
Representation of probabilistic structures and distributions requires the extensive use of lists.
Like higher order entities, lists in OWL languages are second-class citizens in OWL enjoying
minimal support in terms of parsing, reasoning or even editing and construction in the extant
OWL tools. They are implemented in highly complex structures that are difficult to manage
and use.
d) Related to (a), (b), and (c), representation of PRMs in OWL is extremely complicated as
compared to the native syntax of most PRM languages. A PRM that is representable in
twenty lines in a well-suited format could quite conceivably require hundreds or thousands of
lines in OWL_QM. In this sense, OWL_QM is disanalogous with a SWRL extension. Of
course, OWL is designed for machine readability rather than human readability.
Nevertheless, parsimony appears to argue against an OWL implementation of uncertainty
models.
Much of this complexity of structure and bulkiness of model specifications can be hidden from users and
kept in the background. Extant tools for wizard development available in ontology development GUIs
allow us to implement these representational tools with reasonable effort. Nevertheless, it is natural to ask
whether OWL would be the base for semantic web reasoning had it not been for the fact that it was the
language with which development began. An important question to ask here is whether OWL is the
correct foundation for probabilistic representation or whether a more reasonable approach would be to
dismiss the OWL paradigm and introduce or adapt a competing representational paradigm for uncertainty
reasoning in the semantic web context.
If the representational complexity
摘要. Information Extraction and Transport, Inc. (IET) is developing the Knowledge Elicitation
Environment for Probabilistic Event and Entity Relations (KEEPER) system, a tool for eliciting,
storing, updating and implementing probabilistic relational models (PRMs)[1,8,16]. The KEEPER
elicitation component implements a single ontology for the purposes of constraining and guiding
elicitation and providing the semantic bedrock for the reintegration of diverse knowledge sources for
reasoning and learning. We have used an extension of the Web Ontology Language (OWL) to
implement the ontology and the tools for PRM representation, and we describe the main features of that
extension in this paper. This paper offers an informal characterization of OWL_QM, an extension of
OWL that supports the representation of PRMs. It is intended to motivate discussion as to whether
OWL is an appropriate foundation for addressing the challenge of handling uncertainty on the Semantic
Web.
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[推荐]不错的论文：讨论了OWL和Frame-based知识表示的问题，并用概率模型扩展owl
