Fuzzy Knowledge Representation for Fuzzy Systems Based on Fuzzy Ontology on the Semantic Web

2010 ◽  
Vol 159 ◽  
pp. 13-16
Author(s):  
Jun Zhai ◽  
Li Li Qu ◽  
Yan Chen ◽  
Jian Feng Li
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Fuzzy Systems ◽  
Web Applications ◽  
Fuzzy Rule ◽  
Semantic Relationships ◽  
Fuzzy Ontology ◽  
Description Framework ◽  
Fuzzy Linguistic ◽  
Resource Description

Ontology is adopted as a standard for knowledge representation on the Semantic Web, and Resource Description Framework (RDF) is used to add structure and meaning to Web applications. In order to incorporate fuzzy systems into the Semantic Web, this paper utilizes fuzzy ontology to represent formally the fuzzy linguistic variables, considering the semantic relationships between fuzzy concepts. Then fuzzy rule is described as a RDF resource with properties: “IF” and “THEN”, and rule's antecedent and consequent is represented in RDF statement. Taking the fuzzy control system of industrial washing machine for example, the fuzzy system with ontology and RDF is built, which shows that this research enables distributed fuzzy applications on the Semantic Web.

Fuzzy Knowledge Representation Based on Fuzzy Linguistic Variable Ontology and SWRL on the Semantic Web

2011 ◽  
Vol 58-60 ◽  
pp. 1707-1711
Author(s):  
Yan Ling Li ◽  
Yi Duo Liang ◽  
Jun Zhai
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Web Applications ◽  
Fuzzy Rule ◽  
Linguistic Variables ◽  
Semantic Relationships ◽  
Rule Management ◽  
Fuzzy Linguistic Variable ◽  
Fuzzy Linguistic ◽  
Fuzzy Knowledge

Ontology is adopted as a standard for knowledge representation on the Semantic Web, and Ontology Web Language (OWL) is used to add structure and meaning to web applications. In order to share and resue the fuzzy knowledge on the Semantic Web, we propose the fuzzy linguistic variables ontology (FLVO), which utilizes ontology to represent formally the fuzzy linguistic variables and defines the semantic relationships between fuzzy concepts. Then fuzzy rules are described in Semantic Web Rule Language (SWRL) on the basis of FLVO model. Taking a sample case for students’ performance in physics for example, the fuzzy rule management system is built by using the tool protégé and SWRLTab, which shows that this research enables distributed fuzzy applications on the Semantic Web.

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.

Pidgin Metadata Framework as a Mediator for Metadata Interoperability

Libri ◽  
2021 ◽  
Vol 71 (4) ◽  
pp. 375-387
Author(s):  
Seungmin Lee
Keyword(s):  
Structural Characteristics ◽  
Semantic Association ◽  
Semantic Relationships ◽  
Semantic Categories ◽  
External Function ◽  
Layer 2 ◽  
Description Framework ◽  
Internal Function ◽  
Resource Description ◽  
Metadata Interoperability

Abstract A pidgin metadata framework based on the concept of pidgin metadata is proposed to complement the limitations of existing approaches to metadata interoperability and to achieve more reliable metadata interoperability. The framework consists of three layers, with a hierarchical structure, and reflects the semantic and structural characteristics of various metadata. Layer 1 performs both an external function, serving as an anchor for semantic association between metadata elements, and an internal function, providing semantic categories that can encompass detailed elements. Layer 2 is an arbitrary layer composed of substantial elements from existing metadata and performs a function in which different metadata elements describing the same or similar aspects of information resources are associated with the semantic categories of Layer 1. Layer 3 implements the semantic relationships between Layer 1 and Layer 2 through the Resource Description Framework syntax. With this structure, the pidgin metadata framework can establish the criteria for semantic connection between different elements and fully reflect the complexity and heterogeneity among various metadata. Additionally, it is expected to provide a bibliographic environment that can achieve more reliable metadata interoperability than existing approaches by securing the communication between metadata.

scholarly journals Petri nets on the semantic web guidelines and infrastructure

2004 ◽  
Vol 1 (2) ◽  
pp. 127-151 ◽  
Author(s):  
Dragan Gasevic
Keyword(s):  
Semantic Web ◽  
Petri Net ◽  
Ontology Language ◽  
Uml Profiles ◽  
Community Effort ◽  
Model Sharing ◽  
Petri Net Markup Language ◽  
Description Framework ◽  
Definition Of ◽  
Resource Description

This paper gives the Petri net ontology as the most important element in providing Petri net support for the Semantic Web. Available Petri net formal descriptions are: metamodels, UML profiles, ontologies and syntax. Metamodels are useful, but their main purpose is for Petri net tools. Although the current Petri-net community effort Petri Net Markup Language (PNML) is XML-based, it lacks a precise definition of semantics. Existing Petri net ontologies are partial solutions specialized for a specific problem. In order to show current Petri net model sharing features we use P3 tool that uses PNML/XSLT-based approach for model sharing. This paper suggests developing the Petri net ontology to represent semantics appropriately. This Petri net ontology is described using UML, Resource Description Framework (Schema) RDF(S) and the Web Ontology Language-OWL.

Linked Open Statistical Metadata

2017 ◽  
pp. 297-320
Author(s):  
Franck Cotton ◽  
Daniel Gillman
Keyword(s):  
Semantic Web ◽  
Resource Description Framework ◽  
Statistical Data ◽  
Open Data ◽  
Statistical Analyses ◽  
Statistical Literacy ◽  
Statistical Process ◽  
Description Framework ◽  
Resource Description ◽  
The Web

Linked Open Statistical Metadata (LOSM) is Linked Open Data (LOD) applied to statistical metadata. LOD is a model for identifying, structuring, interlinking, and querying data published directly on the web. It builds on the standards of the semantic web defined by the W3C. LOD uses the Resource Description Framework (RDF), a simple data model expressing content as predicates linking resources between them or with literal properties. The simplicity of the model makes it able to represent any data, including metadata. We define statistical data as data produced through some statistical process or intended for statistical analyses, and statistical metadata as metadata describing statistical data. LOSM promotes discovery and the meaning and structure of statistical data in an automated way. Consequently, it helps with understanding and interpreting data and preventing inadequate or flawed visualizations for statistical data. This enhances statistical literacy and efforts at visualizing statistics.

Technique for Transformation of Data From RDB to XML Then to RDF

2017 ◽  
pp. 70-91 ◽  
Author(s):  
Kaleem Razzaq Malik ◽  
Tauqir Ahmad
Keyword(s):  
Semantic Web ◽  
Relational Database ◽  
Resource Description Framework ◽  
Data Science ◽  
True Nature ◽  
Extensible Markup ◽  
Description Framework ◽  
Mapping Techniques ◽  
Resource Description ◽  
The Web

This chapter will clearly show the need for better mapping techniques for Relational Database (RDB) all the way to Resource Description Framework (RDF). This includes coverage of each data model limitations and benefits for getting better results. Here, each form of data being transform has its own importance in the field of data science. As RDB is well known back end storage for information used to many kinds of applications; especially the web, desktop, remote, embedded, and network-based applications. Whereas, EXtensible Markup Language (XML) in the well-known standard for data for transferring among all computer related resources regardless of their type, shape, place, capability and capacity due to its form is in application understandable form. Finally, semantically enriched and simple of available in Semantic Web is RDF. This comes handy when with the use of linked data to get intelligent inference better and efficient. Multiple Algorithms are built to support this system experiments and proving its true nature of the study.

Data Confidentiality on the Semantic Web

2008 ◽  
pp. 3309-3320
Author(s):  
Csilla Farkas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Inference Problem ◽  
Web Technologies ◽  
Ontology Language ◽  
Future Research Directions ◽  
Description Framework ◽  
Resource Description

This chapter investigates the threat of unwanted Semantic Web inferences. We survey the current efforts to detect and remove unwanted inferences, identify research gaps, and recommend future research directions. We begin with a brief overview of Semantic Web technologies and reasoning methods, followed by a description of the inference problem in traditional databases. In the context of the Semantic Web, we study two types of inferences: (1) entailments defined by the formal semantics of the Resource Description Framework (RDF) and the RDF Schema (RDFS) and (2) inferences supported by semantic languages like the Web Ontology Language (OWL). We compare the Semantic Web inferences to the inferences studied in traditional databases. We show that the inference problem exists on the Semantic Web and that existing security methods do not fully prevent indirect data disclosure via inference channels.

Semantic E-Business Challenges and Directions

2011 ◽  
pp. 1421-1428
Author(s):  
Giorgos Laskaridis ◽  
Konstantinos Markellos ◽  
Penelope Markellou ◽  
Angeliki Panayiotaki ◽  
Athanasios Tsakalidis
Keyword(s):  
Semantic Web ◽  
World Wide ◽  
Business Processes ◽  
Semantic Knowledge ◽  
Web Based ◽  
The World ◽  
Extensible Markup ◽  
Description Framework ◽  
Business Challenges ◽  
Resource Description

The emergence of semantic Web opens up boundless new opportunities for e-business. According to Tim Berners-Lee, Hendler, and Lassila (2001), “the semantic Web is an extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation”. A more formal definition by W3C (2001) refers that, “the semantic Web is the representation of data on the World Wide Web. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners. It is based on the resource description framework (RDF), which integrates a variety of applications using eXtensible Markup Language (XML) for syntax and uniform resource identifiers (URIs) for naming”. The capability of the semantic Web to add meaning to information, stored in such way that it can be searched and processed as well as recent advances in semantic Web-based technologies provide the mechanisms for semantic knowledge representation, exchange and collaboration of e-business processes and applications.

scholarly journals RDF 1.1: Knowledge Representation and Data Integration Language for the Web

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 84 ◽  
Author(s):  
Dominik Tomaszuk ◽  
David Hyland-Wood
Keyword(s):  
Knowledge Representation ◽  
Resource Description Framework ◽  
Relational Databases ◽  
Formal Definition ◽  
Natural Languages ◽  
Description Framework ◽  
Generalized Knowledge ◽  
Definition Of ◽  
Resource Description ◽  
The Web

Resource Description Framework (RDF) can seen as a solution in today’s landscape of knowledge representation research. An RDF language has symmetrical features because subjects and objects in triples can be interchangeably used. Moreover, the regularity and symmetry of the RDF language allow knowledge representation that is easily processed by machines, and because its structure is similar to natural languages, it is reasonably readable for people. RDF provides some useful features for generalized knowledge representation. Its distributed nature, due to its identifier grounding in IRIs, naturally scales to the size of the Web. However, its use is often hidden from view and is, therefore, one of the less well-known of the knowledge representation frameworks. Therefore, we summarise RDF v1.0 and v1.1 to broaden its audience within the knowledge representation community. This article reviews current approaches, tools, and applications for mapping from relational databases to RDF and from XML to RDF. We discuss RDF serializations, including formats with support for multiple graphs and we analyze RDF compression proposals. Finally, we present a summarized formal definition of RDF 1.1 that provides additional insights into the modeling of reification, blank nodes, and entailments.

scholarly journals In the Name of the Name: RDF literals, ER attributes and the potential to rethink the structures and visualizations of catalogs

2016 ◽  
Vol 35 (2) ◽  
pp. 19 ◽  
Author(s):  
Manolis Peponakis
Keyword(s):  
Semantic Web ◽  
Conceptual Framework ◽  
Cultural Meanings ◽  
New Approach ◽  
Descriptive Information ◽  
Bibliographic Data ◽  
Er Model ◽  
Description Framework ◽  
Entity Relationship ◽  
Resource Description

<p>The aim of this study is to contribute to the field of machine-processable bibliographic data that is suitable for the Semantic Web. We examine the Entity Relationship (ER) model, which has been selected by IFLA as a “conceptual framework” in order to model the FR family (FRBR, FRAD and RDA), and the problems ER causes as we move towards the Semantic Web. Subsequently, while maintaining the semantics of the aforementioned standards but rejecting the ER as a conceptual framework for bibliographic data, this paper builds on the Resource Description Framework (RDF) potential and documents how both the RDF and Linked Data’s rationale can affect the way we model bibliographic data.</p>In this way, a new approach to bibliographic data emerges where the distinction between description and authorities is obsolete. Instead, the integration of the authorities with descriptive information becomes fundamental so that a network of correlations can be established between the entities and the names by which the entities are known. Naming is a vital issue for human cultures because names are not random sequences of characters or sounds which stand just as identifiers for the entities - they also have socio-cultural meanings and interpretations. Thus, instead of describing indivisible resources, we could describe entities that appear in a variety of names on various resources. In this study, a method is proposed to connect the names with the entities they represent and, in this way, to document the provenance of these names by connecting specific resources with specific names.

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