Modular Knowledge Representation and Reasoning in the Semantic Web

The ISO/HL7 27931:2009 standard intends to establish a global interoperability framework for healthcare applications. However, being a messaging related protocol, it lacks a semantic foundation for interoperability at a machine treatable level intended through the Semantic Web. There is no alignment between the HL7 V2.xml message payloads and a meaning service like a suitable ontology. Careful application of Semantic Web tools and concepts can ease the path to the fundamental concept of Shared Semantics. In this chapter, the Semantic Web and Artificial Intelligence tools and techniques that allow aligned ontology population are presented and their applicability discussed. The authors present the coverage of HL7 RIM inadequacy for ontology mapping and how to circumvent it, NLP techniques for semi-automated ontology population, and the current trends about knowledge representation and reasoning that concur to the proposed achievement.

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Ontological Dimensions of Semantic Mobile Web 2.0

Handbook of Research on Mobility and Computing ◽

10.4018/978-1-60960-042-6.ch042 ◽

2011 ◽

pp. 667-688

Author(s):

Gonzalo Aranda-Corral ◽

Joaquín Borrego-Díaz

Keyword(s):

Social Networks ◽

Semantic Web ◽

Knowledge Representation ◽

Web 2.0 ◽

Point Of View ◽

Knowledge Representation And Reasoning ◽

Mobile Web ◽

New Knowledge ◽

New Challenges

In this chapter, we advance, from the point of view of Knowledge Representation and Reasoning, an analysis of which ontological dimensions are needed to develop Mobile Web 2.0 on top of Semantic Web. This analysis will be particularly focused on social networks and it will try to make an outlook about the new knowledge challenges on this field. Some of these new challenges will be linked to Semantic Web context, while others will be inherent to Semantic Mobile Web 2.0.

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Probabilistic Models for the Semantic Web

The Semantic Web for Knowledge and Data Management ◽

10.4018/978-1-60566-028-8.ch005 ◽

2010 ◽

pp. 74-105 ◽

Cited By ~ 5

Author(s):

Livia Predoiu

Keyword(s):

Semantic Web ◽

Knowledge Representation ◽

Classical Logic ◽

Probabilistic Models ◽

Expressive Power ◽

Knowledge Representation And Reasoning ◽

Uncertain Information ◽

New Approaches ◽

The Web

Recently, there has been an increasing interest in formalisms for representing uncertain information on the Semantic Web. This interest is triggered by the observation that knowledge on the web is not always crisp and we have to be able to deal with incomplete, inconsistent and vague information. The treatment of this kind of information requires new approaches for knowledge representation and reasoning on the web as existing Semantic Web languages are based on classical logic which is known to be inadequate for representing uncertainty in many cases. While different general approaches for extending Semantic Web languages with the ability to represent uncertainty are explored, we focus our attention on probabilistic approaches. We survey existing proposals for extending semantic web languages or formalisms underlying Semantic Web languages in terms of their expressive power, reasoning capabilities as well as their suitability for supporting typical tasks associated with the Semantic Web.

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Knowledge Representation and Reasoning in the Semantic Web

Fuzzy Knowledge Management for the Semantic Web - Studies in Fuzziness and Soft Computing ◽

10.1007/978-3-642-39283-2_1 ◽

2013 ◽

pp. 1-17

Author(s):

Zongmin Ma ◽

Fu Zhang ◽

Li Yan ◽

Jingwei Cheng

Keyword(s):

Semantic Web ◽

Knowledge Representation ◽

Knowledge Representation And Reasoning

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Probabilistic Models for the Semantic Web

Web Technologies ◽

10.4018/978-1-60566-982-3.ch102 ◽

2011 ◽

pp. 1896-1928 ◽

Cited By ~ 3

Author(s):

Livia Predoiu ◽

Heiner Stuckenschmidt

Keyword(s):

Semantic Web ◽

Knowledge Representation ◽

Classical Logic ◽

Probabilistic Models ◽

Expressive Power ◽

Knowledge Representation And Reasoning ◽

Uncertain Information ◽

New Approaches ◽

The Web

Recently, there has been an increasing interest in formalisms for representing uncertain information on the Semantic Web. This interest is triggered by the observation that knowledge on the web is not always crisp and we have to be able to deal with incomplete, inconsistent and vague information. The treatment of this kind of information requires new approaches for knowledge representation and reasoning on the web as existing Semantic Web languages are based on classical logic which is known to be inadequate for representing uncertainty in many cases. While different general approaches for extending Semantic Web languages with the ability to represent uncertainty are explored, we focus our attention on probabilistic approaches. We survey existing proposals for extending semantic web languages or formalisms underlying Semantic Web languages in terms of their expressive power, reasoning capabilities as well as their suitability for supporting typical tasks associated with the Semantic Web

Download Full-text