A hybrid knowledge representation approach to reusability of legal knowledge bases

1995 ◽  
Author(s):  
Ulrich Reimer ◽  
Andreas Margelisch
Keyword(s):  
Knowledge Representation ◽  
Knowledge Bases ◽  
Legal Knowledge ◽  
Hybrid Knowledge

An Overview of Knowledge Representation With Frames

2021 ◽  
pp. 46-63
Author(s):  
Vladislavs Nazaruks ◽  
Jānis Osis
Keyword(s):  
Knowledge Representation ◽  
Knowledge Acquisition ◽  
Hybrid Systems ◽  
Digital Library ◽  
State Of The Art ◽  
Research Work ◽  
Knowledge Bases ◽  
Present Knowledge ◽  
Actual State ◽  
Hybrid Knowledge

Knowledge can be represented in different formats. At present, knowledge representation as ontologies is the mainstream, while much less is heard about frames. In order to understand the state-of-the art of knowledge frames application, the authors overviewed recent research work in IEEE Xplore Digital Library, SpringerLink, ScienceDirect, and ACM Digital Library from 2000 till 2020. The overview touched such aspects as knowledge acquisition techniques, constituent parts of frames, the actual state of technologies used, capabilities of frames integration with other formats, and limitations. The results showed that native limitations of knowledge frames lead to creation of hybrid knowledge bases. However, hybrid systems also have known issues in performance and inconsistency of knowledge due to a conflict between paradigms. Moreover, a large part of technologies mentioned is not supported nowadays. The results can be useful for researchers who investigate whether to use knowledge frames for managing knowledge.

scholarly journals A Modular System Oriented to the Design of Versatile Knowledge Bases for Chatbots

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Giovanni Pilato ◽  
Agnese Augello ◽  
Salvatore Gaglio
Keyword(s):  
Corpus Callosum ◽  
Knowledge Representation ◽  
User Behavior ◽  
Knowledge Bases ◽  
Modular System ◽  
Conversational Agent ◽  
Proof Of Concept ◽  
Conversational Agents ◽  
Specific Domain ◽  
Representation Techniques

The paper illustrates a system that implements a framework, which is oriented to the development of a modular knowledge base for a conversational agent. This solution improves the flexibility of intelligent conversational agents in managing conversations. The modularity of the system grants a concurrent and synergic use of different knowledge representation techniques. According to this choice, it is possible to use the most adequate methodology for managing a conversation for a specific domain, taking into account particular features of the dialogue or the user behavior. We illustrate the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation methodologies and capable of managing different conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, that selects in real time the most adequate chatbot knowledge module to activate.

Web knowledge

2006 ◽  
Author(s):  
Christopher Walton
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Web Applications ◽  
Semantic Network ◽  
Knowledge Bases ◽  
Web Standards ◽  
Description Framework ◽  
The Web

In the introductory chapter of this book, we discussed the means by which knowledge can be made available on the Web. That is, the representation of the knowledge in a form by which it can be automatically processed by a computer. To recap, we identified two essential steps that were deemed necessary to achieve this task: 1. We discussed the need to agree on a suitable structure for the knowledge that we wish to represent. This is achieved through the construction of a semantic network, which defines the main concepts of the knowledge, and the relationships between these concepts. We presented an example network that contained the main concepts to differentiate between kinds of cameras. Our network is a conceptualization, or an abstract view of a small part of the world. A conceptualization is defined formally in an ontology, which is in essence a vocabulary for knowledge representation. 2. We discussed the construction of a knowledge base, which is a store of knowledge about a domain in machine-processable form; essentially a database of knowledge. A knowledge base is constructed through the classification of a body of information according to an ontology. The result will be a store of facts and rules that describe the domain. Our example described the classification of different camera features to form a knowledge base. The knowledge base is expressed formally in the language of the ontology over which it is defined. In this chapter we elaborate on these two steps to show how we can define ontologies and knowledge bases specifically for the Web. This will enable us to construct Semantic Web applications that make use of this knowledge. The chapter is devoted to a detailed explanation of the syntax and pragmatics of the RDF, RDFS, and OWL Semantic Web standards. The resource description framework (RDF) is an established standard for knowledge representation on the Web. Taken together with the associated RDF Schema (RDFS) standard, we have a language for representing simple ontologies and knowledge bases on the Web.

Legal Knowledge Systems

2011 ◽  
pp. 1161-1166 ◽  
Author(s):  
T. F. Gordon
Keyword(s):  
Life Cycle ◽  
Knowledge Bases ◽  
Knowledge Systems ◽  
Information And Communications Technology ◽  
Legal Knowledge ◽  
Levels Of Abstraction ◽  
Research Issues ◽  
Implementation Phase ◽  
Knowledge Based ◽  
Representation Techniques

There are many conceptions of e-governance (Malkia, Anttiroiko, & Savolainen, 2004; Reinermann & Lucke, 2002). Our view is that e-governance is about the use of information and communications technology to improve the quality and efficiency of all phases of the life cycle of legislation. In this conception, computer models of legislation play a central role. We use the term “model” in a broad way, to cover every kind of data model of legislation or metadata about legislation, at various levels of abstraction or detail, including full text, hypertext, diagrams and other visualization methods, and legal knowledge-bases using Artificial Intelligence knowledge representation techniques. The appropriate kind of model depends on the particular task to be supported. In this article, the focus will be on the use of legal knowledge systems (LKS) to support the implementation phase of the life cycle of legislation. Legal Knowledge Systems are also known as legal knowledge-based systems (LKBS). LKS can greatly improve the correctness, consistency, transparency and, last but not least, the efficiency of the administration of complex legislation. The rest of this article is organized as follows. The next section explains the relevance of legal knowledge systems for governance. This is followed by a section motivating the use of LKS to support tasks in the implementation phase of the life cycle of legislation and providing a brief introduction to LKS technology. Next, various application scenarios for implementing public policy and legislation using LKS are discussed. Although research on technology for legal knowledge systems continues, it is a mature technology with many impressive applications in regular use by public administration. The article concludes by reiterating its main points and identifying open research issues.

scholarly journals Efficient Results in Semantic Interoperability for Health Care

2016 ◽  
Vol 25 (01) ◽  
pp. 184-187
Author(s):  
J. Charlet ◽  
L. F. Soualmia ◽  
Keyword(s):  
Health Care ◽  
Semantic Web ◽  
Knowledge Representation ◽  
Large Scale ◽  
Recommendation System ◽  
Clinical Care ◽  
Knowledge Bases ◽  
Semantic Interoperability ◽  
The Third ◽  
Research Activities

Summary Objectives: To summarize excellent current research in the field of Knowledge Representation and Management (KRM) within the health and medical care domain. Method: We provide a synopsis of the 2016 IMIA selected articles as well as a related synthetic overview of the current and future field activities. A first step of the selection was performed through MEDLINE querying with a list of MeSH descriptors completed by a list of terms adapted to the KRM section. The second step of the selection was completed by the two section editors who separately evaluated the set of 1,432 articles. The third step of the selection consisted of a collective work that merged the evaluation results to retain 15 articles for peer-review. Results: The selection and evaluation process of this Yearbook’s section on Knowledge Representation and Management has yielded four excellent and interesting articles regarding semantic interoperability for health care by gathering heterogeneous sources (knowledge and data) and auditing ontologies. In the first article, the authors present a solution based on standards and Semantic Web technologies to access distributed and heterogeneous datasets in the domain of breast cancer clinical trials. The second article describes a knowledge-based recommendation system that relies on ontologies and Semantic Web rules in the context of chronic diseases dietary. The third article is related to concept-recognition and text-mining to derive common human diseases model and a phenotypic network of common diseases. In the fourth article, the authors highlight the need for auditing the SNOMED CT. They propose to use a crowd-based method for ontology engineering. Conclusions: The current research activities further illustrate the continuous convergence of Knowledge Representation and Medical Informatics, with a focus this year on dedicated tools and methods to advance clinical care by proposing solutions to cope with the problem of semantic interoperability. Indeed, there is a need for powerful tools able to manage and interpret complex, large-scale and distributed datasets and knowledge bases, but also a need for user-friendly tools developed for the clinicians in their daily practice.

COMBINING DEFAULT LOGIC DATABASES

1994 ◽  
Vol 03 (03) ◽  
pp. 319-348 ◽  
Author(s):  
CHITTA BARAL ◽  
SARIT KRAUS ◽  
JACK MINKER ◽  
V. S. SUBRAHMANIAN
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
Large Scale ◽  
Future Generation ◽  
Knowledge Bases ◽  
Default Logic ◽  
Integrity Constraints ◽  
Specialized Knowledge ◽  
The Past ◽  
The Future

During the past decade, it has become increasingly clear that the future generation of large-scale knowledge bases will consist, not of one single isolated knowledge base, but a multiplicity of specialized knowledge bases that contain knowledge about different domains of expertise. These knowledge bases will work cooperatively, pooling together their varied bodies of knowledge, so as to be able to solve complex problems that no single knowledge base, by itself, would have been able to address successfully. In any such situation, inconsistencies are bound to arise. In this paper, we address the question: "Suppose we have a set of knowledge bases, KB1, …, KBn, each of which uses default logic as the formalism for knowledge representation, and a set of integrity constraints IC. What knowledge base constitutes an acceptable combination of KB1, …, KBn?"

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