A Semantic Web Pragmatic Approach to Develop Clinical Ontologies, and thus Semantic Interoperability, based in HL7 v2.xml Messaging

2013 ◽  
pp. 205-214 ◽  
Author(s):  
David Mendes ◽  
Irene Pimenta Rodrigues
Keyword(s):  
Artificial Intelligence ◽  
Semantic Web ◽  
Knowledge Representation ◽  
Ontology Mapping ◽  
Knowledge Representation And Reasoning ◽  
Healthcare Applications ◽  
Current Trends ◽  
Web Tools ◽  
Ontology Population ◽  
Tools And Techniques

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.

Ontological Dimensions of Semantic Mobile Web 2.0

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.

Probabilistic Models for the Semantic Web

2010 ◽  
pp. 74-105 ◽  
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.

scholarly journals A Brief Overview of Artificial Intelligence in South Africa

AI Magazine ◽  
2012 ◽  
Vol 33 (1) ◽  
pp. 99-103 ◽  
Author(s):  
Alexander Ferrein ◽  
Thomas Meyer
Keyword(s):  
Artificial Intelligence ◽  
South Africa ◽  
Knowledge Representation ◽  
Computational Intelligence ◽  
Mobile Robotics ◽  
Current Level ◽  
Knowledge Representation And Reasoning ◽  
Human Language ◽  
Language Technologies

One of the consequences of the growth in AI research in South Africa in recent years is the establishment of a number of research hubs involved in AI activities ranging from mobile robotics and computational intelligence, to knowledge representation and reasoning, and human language technologies. In this survey we take the reader through a quick tour of the research being conducted at these hubs, and touch on an initiative to maintain and extend the current level of interest in AI research in the country.

Artificial Intelligence-Based Knowledge Representation and Reasoning

2021 ◽  
pp. 134-149
Author(s):  
Dimpal Tomar ◽  
Pradeep Tomar
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Knowledge Representation ◽  
Knowledge Bases ◽  
Knowledge Representation And Reasoning ◽  
Artificial Intelligent ◽  
Logical Interpretation ◽  
Quality Of Higher Education ◽  
The Right

The quality of higher education can be enhanced only by upgrading the content and skills towards knowledge. Hence, knowledge representation and reasoning play a chief role to represent the facts, beliefs, and information, and inferring the logical interpretation of represented knowledge stored in the knowledge bases. This chapter provide a broad overview of knowledge, representation, and reasoning along with the related art of study in the field of higher education. Various artificial intelligent-based knowledge representation and reasoning techniques and schemes are provided for better representation of facts, beliefs, and information. Various reasoning types are discussed in order to infer the right meaning of the knowledge followed by various issues of knowledge representation and reasoning. .

Semantic Web Tools and Techniques for Knowledge Organization: An Overview

2017 ◽  
Vol 44 (4) ◽  
pp. 273-290 ◽  
Author(s):  
Thimmaiah Padmavathi ◽  
Madaiah Krishnamurthy
Keyword(s):  
Semantic Web ◽  
Knowledge Organization ◽  
Web Tools ◽  
Tools And Techniques

scholarly journals Model-theoretic Characterizations of Existential Rule Languages

2020 ◽  
Author(s):  
Heng Zhang ◽  
Yan Zhang ◽  
Guifei Jiang
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Representation ◽  
Computer Science ◽  
Model Theory ◽  
Deep Understanding ◽  
Knowledge Representation And Reasoning ◽  
Complexity Bounds ◽  
Rule Languages ◽  
Finite Structures

Existential rules, a.k.a. dependencies in databases, and Datalog+/- in knowledge representation and reasoning recently, are a family of important logical languages widely used in computer science and artificial intelligence. Towards a deep understanding of these languages in model theory, we establish model-theoretic characterizations for a number of existential rule languages such as (disjunctive) embedded dependencies, tuple-generating dependencies (TGDs), (frontier-)guarded TGDs and linear TGDs. All these characterizations hold for the class of arbitrary structures, and most of them also work on the class of finite structures. As a natural application of these results, complexity bounds for the rewritability of above languages are also identified.

scholarly journals Knowledge Representation and Reasoning — A History of DARPA Leadership

AI Magazine ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 9-21
Author(s):  
Richard Fikes ◽  
Tom Garvey
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Representation ◽  
Knowledge Representation And Reasoning ◽  
Research Projects ◽  
Artificial Intelligence Research ◽  
Fundamental Goal ◽  
Computational Support ◽  
Intelligent Behavior ◽  
History Of ◽  
The Impact

A fundamental goal of artificial intelligence research and development is the creation of machines that demonstrate what humans consider to be intelligent behavior. Effective knowledge representation and reasoning methods are a foundational requirement for intelligent machines. The development of these methods remains a rich and active area of artificial intelligence research in which advances have been motivated by many factors, including interest in new challenge problems, interest in more complex domains, shortcomings of current methods, improved computational support, increases in requirements to interact effectively with humans, and ongoing funding from the Defense Advanced Research Projects Agency and other agencies. This article highlights several decades of advances in knowledge representation and reasoning methods, paying particular attention to research on planning and on the impact of the Defense Advanced Research Projects Agency’s support.

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