This is where ontologies, extra rules, etc, may come in force. Knowledge representation iii ontologies and applications. W176 chapter 18 knowledge acquisition, representation, and reasoning 2. Citeseerx knowledge representation and ontologies logic. Representing ontologies and integrating them with rules. Ontologies and knowledge sharing knowledge based systems and services are expensive to build, test, and maintain. A software engineering methodology based on formal specifications of shared resources, reusable components, and standard services is. Representing strategic organizational knowledge via diagrams. A knowledge representation language is defined by two aspects.
It simply has to do with writing down, in some language or communicative. There is an assumption commonly embraced by ontological engineers, an. A great deal of research has been done to make the corpora of knowledge available for machines. The main objective of this paper is to survey some of the basic concepts that have been used in computer science for the representation of knowledge and summarize some of their advantages and drawbacks. The object of a knowledge representation is to express knowledge in a computer tractable form, so that it can be used to enable our ai agents to perform well. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and framebased ontologies. Aligning and merging existing ontologies, which is usually handled manually, often constitutes a large and tedious portion of the sharing process. Sambo a system for aligning and merging biomedical. Knowledge in expert systems knowledge representation is key to the success of expert systems. This approach has several advantages shown in the study, but also some drawbacks related to state of the art technologies. Cnls typically support bidirectional mapping to some formal language like firstorder logic fol or its decidable subset owl dl kaljurand and fuchs, 2006 that allows to apply existing tools for reasoning, consistency checking or. Ontologies a ect the whole lifecycle of the information system. Previous classification of laws and cases accordingly with.
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge based system. Chapter knowledge 18 acquisition, representation, and reasoning. After introducing ontologies in terms of their appearance, usage and classification, it addresses concrete ontology languages that are particularly important in the context of the semantic web. Proceedings of the ijcai01 workshop on ontologies and. Towards automatic knowledge acquisition from text based. Disjointknowledge analysis and preservation in ontology. From legal texts to legal ontologies and questionanswering systems 12 motivation access to laws or court decisions fire track adhoc retrieval from legal documents adapted u. Applications of ontologies in knowledge representation of. This paper describes two important contributions to obtain better advantages of the web resources. A good knowledge representation enables fast and accurate access to knowledge and understanding of the content. A translation approach to portable ontology specifications. Towards automatic knowledge acquisition from text based on ontologycentric knowledge representation and acquisition yusheng lai industrial technology research institute.
We add bridging axioms not only as \bridges between concepts in two related ontologies but also to make this merge into a new ontology for further merging with other ontologies. From terminologies to ontologies advances in knowledge. Ontologies have become important tools in biomedicine, supporting critical aspects of both health care and biomedical research, including clinical research 1. For the sake of simplicity, our examples will use isa. A realist framework for ontologies and the semantic web. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Concepts, ontologies, and knowledge representation grega. Im searching for situations where someone divorced because the husbandwife left home. Conceptual knowledge processing with formal concept analysis. We could add extra knowledge to the merged datasets e. Target representation and background knowledge for discovery from facts.
The resulting knowledge graph was converted into rules acceptable to g2. Pdf concepts, ontologies, and knowledge representation. Iowa state university department of computer science artificial intelligence research laboratory semantic web technology ontologies establish a formal semantics for data and knowledge making it possible for computers to process information. However, knowledge about ontologies in ka2 was represented so as to allow one to distinguish ontologies from other ka research topics. Knowledge of schedules, raw materials, labor, manufacturing and distribution is essential to the supply chain while knowledge of customer interests. Knowledge representation and reasoning logics for arti cial. Disjoint knowledge analysis and preservation in ontology merging process muhammad fahad1,2, nejib moalla1, abdelaziz bouras1 muhammad abdul qadir2, muhammad farukh2 1university of lyon2 cerral iutlumiere lyon ii, bron, france 2center for distributed and semantic computing, m. Knowledge representation and reasoning logics for arti cial intelligence stuart c. Research in knowledge representation aims to share the information among systems. We will provide a general approach for handling these two essential issues within the ontologging architecture. Communicating data and knowledge between humans and computers vasant honavar, 2006. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts.
Knowledge representation techniques like semantic networks and ontologies make this possible. Managing multiple ontologies and ontology evolution in. Ontologies representation and management, as a semantic tool for organizational memory consolidation according to its common definition, an ontology defines terms and concepts or meanings employed to describe and depict an area or domain of knowledge. As researchers in the ontologydesign field develop the content of a growing number of ontologies, the need for sharing and reusing this body of knowledge becomes increasingly critical. Proceedings of the ijcai01 workshop on ontologies and information sharing a.
There has been a great deal of research and development in this area combined with hype and reaction. Knowledge affects the development, efficiency, speed, and maintenance of the system. Knowledge representation, the foundation of intelligent systems introduction knowledge is a decisive competitiveadvantage for todays corporations. Translation of ontologies is a very important and dif. Our uniform internal representation, webpddl, is a strong. Knowledge base ontologies permission to make digital or hard copies of all or part of this work for. Therefore, this knowledge was introduced for ontologies described as products. Knowledge representation and 1reasoning hector e j. Merge ontologies and rules into a single representation. Mind map provides information about a topic that is structured in a tree see fig. Hierarchical course knowledge representation using ontologies. The interviews resulted in 10 different knowledge sets, represented as graphs.
A separate section to each of the above topics is dedicated followin g a uniform outline. In artificial intelligence, knowledge representation studies the formalisation of knowledge and its processing within machines. In computer science and information science, an ontology encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities that substantiate one, many or all domains of discourse. Ontologies and knowledge representation a domain ontology 9 ontologies and knowledge representation categories of formal ontologies axiomatized ontology. The growing web information makes a heavy computational load on the system which has to be designed to translate, merge, integrate, access, manipulate and maintain the web information5. Towards automatic knowledge acquisition from text based on. This paradigm could be memorized by a rule named start skos, grow big.
We merge two ontologies when we, based on the alignment relationships between the. Introduction people cant share knowledge if they do not speak a common language 7. A family of logic based knowledge representation formalisms descendants of semantic networks and klone brachman and schmolze, 1985 describe domain in terms of concepts classes, roles relationships and individuals distinguished by. A new notation to represent knowledge using ontologies, called om on. Ontology as reality representation barry smith department of philosophy, university at buffalo, ny 14260, usa institute for formal ontology and medical information science, saarland university, 66041 saarbrucken, germany abstract. Knowledge management, ontology mapping, ontology evolution. The present and future recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic web, businesstobusiness applications, and. Modeling information through ontologies ontologies in information systems the role of ontologies in information systems goes beyond that of conceptual schemas. Pdf applications of ontologies in knowledge representation. The knowledge acquisition process leads to a domain conceptualisation.
Levesque department of computer science, university of toronto, toronto, ontario m5s ia4 canada the notion of a representation of knowledge is at heart easy to understand. Distributed semantic web knowledge representation and. A separate section to each of the above topics is dedicated following a uniform outline. Formal refers to the fact that an ontology is a form of knowledge representation and has a formal software specification to represent such conceptualisations, for example, an ontology has to be machinereadable. National library of medicine, bethesda, maryland, usa. The latter process is often termed ontology merging, and will be discussed herein. Ontologies, with the associated reasoning capabilities and inference tools.
In this work structure of medical ontologies and their construction process are presented. Concepts, ontologies, and knowledge representation ebook by. A wide variety of tasks in diverse research areas are supported by ontologies. The poolparty knowledge modelling approach suggests to start first with skos to further extend this simple knowledge model by other knowledge graphs, ontologies and annotated documents and legacy data. Hierarchical course knowledge representation using. Concepts, ontologies, and knowledge representation. Chapter 2 an introduction to ontologies and ontology engineering. Query answering in databases and ontologies diego calvanese faculty of computer science master of science in computer science a. Query answering in databases and ontologies diego calvanese faculty of computer science master of science in computer science. A separate chapter is dedicated to each of the three introduced topics, following. Distributed semantic web knowledge representation and inferencing harold boley unb, faculty of computer science. Other knowledge elicitation and acquisition methods can be applied, such as the techniques to build knowledge based systems. On the lower left is an icon that resembles a person named john.
In order to get a first idea about the meaning of the term ontology, an. This chapter gives an overview on basic knowledge representation aspects and on ontologies as used within computer systems. Formal semantics typically model theoretic decidable fragments of fol. Syntax the syntax of a language defines which configurations of the components. Knowledge representation and ontologies springerlink. Ontologies have become the knowledge representation medium of choice in recent years for a range of computer science specialities including the semantic web, agents, and bioinformatics. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline. Mind map mind map were originally developed to support more efficient learning and evolved to a management technique used by numerous companies buzan 1974. Modeling information through ontologies ontologies description logics provide the formal foundations for ontology languages. The present and future knowledge representation with ontologies.
Towards automatic knowledge acquisition from text based on ontologycentric knowledge representation and acquisition yusheng lai industrial technology research institute, tainan, taiwan, r. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and. The aim of medical knowledge representation is to capture the detailed domain knowledge in a clinically efficient manner and to offer a reliable resolution with the acquired knowledge. An information systems perspective 383 model, and to allow computation based on the semantics of those terms, i. The reference ontology, which reused ka, introduced knowledge that allowed one ontology to be distinguished from another. Such multi representation capabilities for organizational knowledge are already supported by some enterprise architecture management software tools. Expert systems are designed for knowledge representation based on rules of logic called inferences. Sambo a system for aligning and merging biomedical ontologies patrick lambrix and he tan. Uniform knowledge representation model, consisting of ontologies that are populated by concepts. Toward principles for the design of ontologies used for.
Selected design decisions are discussed, and alternative representation choices and evaluated against the design criteria. Knowledge management research focuses on the development of concepts, methods, and tools supporting the management of human knowledge. Concepts, ontologies, and knowledge representation ebook. Ontologies in medical knowledge representation alan jovic, marin prcela, dragan gamberger rudjer boskovic institute, laboratory of informational systems, email. From taxonomies over ontologies to knowledge graphs. For example, in this paper we develop an ontology of wine and. Therefore, there is a crucial need to merge these ontologies which is abstract and a challenge. Applications of ontologies in knowledge representation of human perception article pdf available in international journal of metadata semantics and ontologies 91. Knowledge representation iii description logics and ontologies. Techniques of automated reasoning allow a computer system to draw conclusions from knowledge represented in a machineinterpretable form. There exists knowledge represented by various ontologies which are scattered and therefore makes analysis and usage a difficult task. Representational adequacy the ability to representall kinds of knowledge that are needed in that domain. The speci cation of an ontology usually comprises two distinct levels.
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