Fuzzy logic, semantic web languages, rdfs, owl, rif. Swrlf a fuzzy logic extension of the semantic web rule language. The rule structure of both types are the same, except for the antecedent and consequent are of the respective types. The semantic web is an extension of the world wide web through standards set by the world. Developing a fuzzy search engine based on fuzzy ontology. In fact, fuzzy logic cannot be ignored in order to bridge the gap between humanunderstandable soft logic and machinereadable hard logic. It is noted that the fuzzy logic is also one of the most effective techniques in ai, which provides a computational framework for. Fuzzy logic, annotation domains and semantic web languages umberto straccia isticnr, pisa, italy.
This talk presents a detailed, selfcontained and comprehensive account of the state of the art in representing and reasoning with fuzzy knowledge in semantic web languages such a rdfrdfs, owl 2 and rif and discuss some implementation related issues. Logic tensor networks for semantic image interpretation ivan donadello fondazione bruno kessler and university of trento. Despite the existing research work the problem of supplementing sw with fl remains without implemented, generic, publicly available, standardsbased and widely used solution. Enhancing semantic search engine by using fuzzy logic in web mining. Fuzzy ontology introduces fuzzy logical rules in ontology for representing imprecise domain. Foundations of fuzzy logic and semantic web languages provides a rigorous and succinct account of the mathematical methods and tools used for representing an. Automatic fuzzy ontology generation for semantic web ieee xplore.
Reasoning over decomposing fuzzy description logic. Fuzzy ontologies for the semantic web springerlink. Processing fuzzy information in semantic web applications 335 some of the mentioned issues are candidates being solved by fuzzy logic. In this paper we present a hybrid measure of semantic word similarity using fuzzy inference system which combines both the corpus based distance measures as well as gloss overlap to get the final similarity between two words. This looks at the semantic web design in the light a little reading on formal logic, of the access limited logic system, in particular, and in the light of logical languages in general.
Fuzzy description logics combines fuzzy logic with dls. The web ontology language owl uses again a different terminology, also given in. A physical cognitive city differs from conventional cities and smart cities in the fact that it is steadily learning through constant interaction with its citizens through advanced information and. Fuzzy logic can be incorporated to ontology to represent uncertainty information. The fuzzy go search engine can thus automatically retrieve web pages that contain synonyms or terms similar to keywords. The aim of this chapter is to present a detailed, selfcontained and comprehensive account of the state of the art in representing and reasoning with fuzzy knowledge in semantic web languages such as triple languages rdfrdfs, conceptual languages of the owl 2 family and rule languages. Enhancing semantic web technologies with an ability to express. To enable the encoding of semantics with the data, technologies such as resource description framework rdf 2 and web ontology language owl 3 are used. Description logics dl are a family of formal knowledge representation languages. Semweb is a lowlevel api facilitating access into rdfxml owl ontologies from. Fuzzy role based access control design using fuzzy ontology. Cognitive city is a term which expands the concept of the smart city with the aspect of cognition or refers to a virtual environment where goaldriven communities gather to share knowledge. A fuzzy logic semantic mapping approach for fuzzy geospatial ontologies.
Using fuzzy logic in uncertain information increases the semantic web power. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new wiley online library account. The goal of the semantic web is to make internet data machinereadable. A survey on fuzzy ontologies for the semantic web the knowledge. Hvkrzwrglvsod\ web resources for human consumption, that will be enhanced with semantic markups often called annotations. Request pdf an overview of fuzzy description logics for the semantic web information imprecision and uncertainty exist in many real world applications, and such information would be retrieved. The publication capturing intelligence, volume 1, discusses the positive role of fuzzy logic, and soft computing in the development of the semantic web, by filling a gap, and facing a new challenge. Nicholas sheble the concept of fuzzy logic comes in to the life 35. Fuzzy rolebased access control frbac is essential for riskbased environments in many futuristic applications, even though rolebased access control rbac is the efficient and widely used. Fuzzy dls are able to represent vague concepts such as a tall person, a hot place, a middleaged person, a near destination and many more. The topics of this book include fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology knowledge bases, extraction of fuzzy description logics and ontologies from fuzzy data models, storage of fuzzy ontology knowledge.
One way to use the the fuzzy logic approach for the classi. Swrlf a fuzzy logic extension of the semantic web rule language tomasz wiktor wlodarczyk1, martin oconnor2, chunming rong1, mark musen2, 1 university of stavanger, norway. Our aim here is not to give implementation details of the latter, but to use the example to explain the underlying fuzzy logic. Any event, process, or function that is changing continuously cannot always be defined as either true or false, which means that we need to define such activities in a fuzzy manner. Journal of the american society for information science and technology. From a logical point of view, we may model uncertain fuzzy sentences in the following. Uncertainty and the semantic web giorgos stoilos 1, giorgos stamou, vassilis tzouvaras, je. I am trying to learn the difference in order to implement type ii fuzzy logic with semantic web technology to help increase the number of relevant search results.
In this paper we present swrlf, a fuzzy logic extension of the semantic web rule language. It is presented several connections between fuzzy logic, the semantic web, and its. This is a wellknown problem especially for semanticsbased applications. Volume 58, issue 14, pages 24092410, issue 14, pages 24092410. Pan 2and ian horrocks 1 department of electrical and computer engineering, national technical university of athens, zographou 15780, greece 2 school of computer science, the university of manchester manchester, m 9pl, uk abstract. Managing vaguenessfuzziness is starting to play an important role in semantic web research, with a large number of research efforts underway. Please help me understand the difference by giving simple examples. To tackle this problem, this paper proposes the foga fuzzy ontology.
Fuzzy logic, knowledge representation, semantic web, rdf, rdf schema. A hybrid approach using ontology similarity and fuzzy logic. A fuzzy set theory corresponds to fuzzy logic and the semantic of fuzzy operators can be understood using a geometric model. Foundations of fuzzy logic and semantic web languages. R russell rhine heart, head, chemical engineering school, oklahoma state university, first declared that the fuzzy logic term is originally nonsensical 25. Fuzzy logic is a form of manyvalued logic in which the truth values of variables may be any real.
Extending fuzzy description logics for the semantic web. Lotfi zadeh, the father of fuzzy logic, claimed that many vhwv in the world that surrounds us are defined by a nondistinct boundary. Download book pdf soft computing in ontologies and semantic web pp 149209 cite as. One task we now have is to clarify such notions as \valid inference in a language and \correct for a language.
Towards a fuzzy description logic for the semantic web, the semantic web. Ontology is an effective conceptualism commonly used for the semantic web. Fuzzy logic and the semantic web zhu 2007 journal of. We show that this new measure reasonably correlates to human judgments and the average. The topics of this book include fuzzy description logics and fuzzy ontologies, queries. Soft computing in ontologies and semantic web springerlink. Fuzzy description logics fuzzy dls and fuzzy owl have been proposed as languages able to represent and reason about imprecise. Fuzzy logic will not supposed to be the basis for the semantic web but its related concepts and techniques will certainly reinforce the systems classically developed within w3c. In situations which we face uncertainty in knowledge and there is no specific boundaries between concepts, it is not enough to use ontology for concept formalization and thus classical logical methods for uncertain information investigation is not enough. Nowadays, in ontologybased applications information is often vague and imprecise. In fact, fuzzy logic cannot be ignored if we are to bridge the gap between humanunderstandable soft logic and machinereadable hard logic. View the article pdf and any associated supplements and figures for a period of 48 hours. Pdf ontologies are not only crucial for extending the traditional web into the semantic web but also for.
Semantic web ontologies are based on crisp logic and do not provide welldefined means for expressing imperfection. By making this type of evaluation, usually done by an experienced operator, fewer rules can be evaluated, thus simplifying the processing logic and perhaps even improving the fuzzy logic system. That is, the classification of attribute values are fuzzy e. Dllearner a framework for inductive learning on the. Bobillo from fuzzy to annotated sw languages 2 239. Typically, fuzzy ontology is generated from a predefined concept hierarchy. Knowledge representation using semantic net and fuzzy logic. For example, ontology can describe concepts, relationships between entities. These keywords were added by machine and not by the authors. Automatic fuzzy ontology generation for semantic web. Ontologies are not only crucial for extending the traditional web into the semantic web but also for developing intelligent. In the current paper we present a fuzzy extension to the dl shin. Fuzzy logic is the most common technique for dealing with vagueness. To enable the encoding of semantics with the data, technologies such as resource description framework rdf and web ontology language owl are used.
Patrick hayes 1 introduction a major international research e ort is currently under way to improve the existing world wide web www, with the intention to create what is often called the semantic web bernerslee et al. The fuzzy logic concept is simple but the jargon obscure that because fuzzy logic concept is totally. Later the semantics of fuzzy logic is more formally introduced for the purposes of querying over rdf triples 21 with the use of tnorms and r. A selfcontained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic environments, and other applications have emerged. Towards a fuzzy description logic for the semantic web. How to represent non crisp data, such as an expensive book, a good customer within the ontology definition. However, an arbitrary choice table does not always define a fuzzy logic function. Net component intended to work with fuzzy logic sets and relations 11.
Semantic web for the working ontologist modeling in rdf, rdfs and owl dean allemang james hendler amsterdam boston heidelberg london new york oxford paris san diego san francisco morgan kaufmann publishers is an imprint of elsevier singapore sydney tokyo. Fuzzy logic and the semantic web, volume 1 1st edition elsevier. We further show to which extend we may generalise them to socalled annotation domains, that cover also e. We use wordnet as a lexical dictionary to get semantic information about words. Logics for the semantic web pascal hitzler, jens lehmann, axel polleres reader. Extending fuzzy description logics for the semantic web giorgos stoilos 1and giorgos stamou department of electrical and computer engineering, national technical university of athens, zographou 15780, greece abstract. The semantic web is an extension of the world wide web through standards set by the world wide web consortium w3c. Explorers guide to the semantic web, p 4 the semantic web is a vision of the next generation web, which. Because fuzzy logic was conceived to find solutions to the problems of inaccuracies and uncertainties in a flexible way, researchers have had the idea to integrate this logic in the field of the semantic web in general and to use it in the construction of ontologies by the logic of description in particular.
The semantics of predicate logic university of waterloo. An overview of fuzzy description logics for the semantic web. A problem here is a that i am no logician, and so i am am having to step like a fascinated reporter into this world of which i do not possess intimate experience. Fuzzy logic, annotation domains and semantic web languages. Fuzzy knowledge management for the semantic web zongmin ma. Fuzzy logic and the semantic web volume 1 capturing. It discusses the concepts, tools, techniques, and applications exhibiting the usefulness, and the necessity, of using fuzzy logic in the semantic web. From fuzzy to annotated semantic web languages springerlink. First, a fuzzy ontology is constructed by using fuzzy logic to capture the similarities of terms in the ontology, which offering appropriate semantic distances between terms to accomplish the semantic search of keywords. Foundations of fuzzy logic and semantic web languages 1st.
Received 5 november 2016 received in revised form 12 january 2017 accepted 12 january 2017 final year projects fyp is the pinnacle to test the practical and research skills of undergraduate students before they enter the workforce. The kr languages used rdf, rdf schema and owl have the character. The idea of fuzzy set and fuzzy logic theory was first proposed by zadeh zadeh, 75, as a mean of handling. Tightly integrated fuzzy description logic programs under the. Semantic web for the working ontologist modeling in rdf, rdfs and owl dean allemang james hendler amsterdam boston heidelberg london new york oxford paris san diego san francisco morgan kaufmann publishers is an imprint of elsevier. Dllearner a framework for inductive learning on the semantic web lorenz buhmann a, jens lehmannb, patrick westphal auniversity of leipzig, institute of computer science, aksw group, augustusplatz 10, d04009 leipzig, germany. Fuzzy systems is an alternative to traditional notions of set membership and logic that has its origins in. The word fuzzy refers to things which are not clear or are vague. The aim of ths study is to enhance the desgn evauaton and. This book goes to great depth concerning the fast growing topic of technologies and approaches of fuzzy logic in the semantic web.
There are two features of description logic that are not shared by most other data. The present work describes system architecture of a collaborative approach for semantic search engine mining. There is no way to say this is a catalog or even to establish that acme. This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing e. Enhancing semantic search engine by using fuzzy logic in web. Swrlf a fuzzy logic extension of the semantic web rule. Fuzzy logic and the semantic web capturing intelligence. Semantic web languages swl are the languages used to provide a. Figure 1 from implementation of fuzzy logicbased final. The fora framework a fuzzy grassroots ontology for. Logic tensor networks for semantic image interpretation. The main difference between them is that the type2 fuzzy set itself is fuzzy, with a new dimension called the footprint of uncertainty, which characterizes type2 fuzzy logic. Silvia calegari, elie sanchez, a fuzzy ontologyapproach to improve semantic information retrieval, proceedings of the third international conference on uncertainty reasoning for the semantic web, p. It is presented several connections between fuzzy logic, the semantic web, and its components ontologies, description logics.
We know that logic is the basis of reasoning and fuzzy logic extends the capability of reasoning by using fuzzy predicates, fuzzypredicate modifiers, fuzzy quantifiers and fuzzy qualifiers in fuzzy propositions which creates the difference from classical logic. Foundations of fuzzy logic and semantic web languages provides a rigorous and succinct account of the mathematical methods and tools used for representing and reasoning with fuzzy information within semantic web languages. Download it once and read it on your kindle device, pc, phones or tablets. But if the question raised above has a right answer, it would seem that in formal semantics we ought to consider. The vision of the semantic web is to let computer software relieve us of much of the burden of locating resources on the web that are relevant to our needs and extracting, integrating and indexing the information contained within. However, it is widely pointed out that classical ontology model is not sufficient to deal. What is difference between type 1 and type 2 fuzzy logics. The author focuses on the social web and possibilities of its integration with the semantic web as resource for a semiautomated tracking of online reputations using imprecise natural language terms. Fuzzy logic will not be the basis for the semantic web but its related concepts and techniques will certainly reinforce the systems classically developed within w3c. Boolean logic, and the latter 2 is suitable for a fuzzy controller using fuzzy logic. Chapter 16 processing fuzzy information in semantic web. Resource finding, information selection and preprocessing, generalization and analysis. Semantics, algebras, and derivation systems kindle edition by merrie bergmann.
The geometric visualization of fuzzy logic will give us a hint as to the possible connection with neural. These technologies are used to formally represent metadata. Semantic web rule language is a combination of the owl dl and owl lite sublanguages with the unarybinary datalog ruleml sublanguages of the rule markup language fuzzy logic is a form of multivalued logic, which derived from the fuzzy set theory introduced by zadeh extends binary set by adding a degree of membership. It is then introduced and illustrated by an example ontology of art a fuzzy ontology structure, lexicon and knowledge base. Foundations of fuzzy logic and semantic web languages crc.
Net operators, so that one can effortlessly build and evaluate fuzzy logic expressions directly in. Fuzzy logic and associated concepts and techniques more generally, soft computing, has certainly a positive role to play in the development of the semantic web. However, to construct a concept hierarchy for a certain domain can be a difficult and tedious task. The inherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzzy logic and the semantic web, volume 1 1st edition. The book focuses on the three main streams of semantic web languages. Towards a fuzzy description logic for the semantic web 169 equal to 20.
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