Implementasi Semantic Web Rule Language dalam Pemberian Rekomendasi Nutrisi Berbasis Ontologi

CCIT Journal ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 207-217
Author(s):  
Dirko G. S. Ruindungan ◽  
Christopel H. Simanjuntak
Keyword(s):  
Semantic Web ◽  
Domain Knowledge ◽  
Nutrient Content ◽  
Energy Estimates ◽  
The Internet ◽  
Maternal Condition ◽  
Food Ingredients ◽  
Distinct Source ◽  
Nutritional Recommendation ◽  
Semantic Web Rule Language

The recommendations or guidelines about nutrition are available from a various distinct source on the internet. On the other hand, nutritional information needed by each person is different according to physical condition or personal preferences of each individual. This becomes a bit complicated because every information provider on the internet has a different understanding in giving foodstuff references to certain nutrients. In this study, an ontology in nutrition domain knowledge was used. The ontology represents explicit specification of pregnancy nutrition domain knowledge. The ontology constructed consists of three basic concepts that is Person, Maternal Condition and PrenNutriFood. To support the provision of nutritional recommendation, three definitions were added to ontology that is determining energy estimates per day, determining the percentage of daily value (DV) of food ingredients and determining the claims of nutrient content in foodstuff. In this study, we implemented the Semantic Web Rule Language to formalize those definitions. Inference from each rule is generated through Pellet as an inference engine. Ontology has been successfully managed with rules and finally produce new knowledge containing the recommendations. The results of inference indicate the expansion of knowledge in ontology

How Industry 4.0 Can Benefit From Semantic Web Technologies and Artefacts

2021 ◽  
Vol 13 (4) ◽  
pp. 64-74
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Semantic Web ◽  
Industry 4.0 ◽  
The Internet ◽  
Time Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Real Time Data ◽  
The Internet Of Things

Industry 4.0 is a technology-driven manufacturing process that heavily relies on technologies, such as the internet of things (IoT), cloud computing, web services, and big real-time data. Industry 4.0 has significant potential if the challenges currently being faced by introducing these technologies are effectively addressed. Some of these challenges consist of deficiencies in terms of interoperability and standardization. Semantic Web technologies can provide useful solutions for several problems in this new industrial era, such as systems integration and consistency checks of data processing and equipment assemblies and connections. This paper discusses what contribution the Semantic Web can make to Industry 4.0.

Discovering Complex Relationships of Drugs over Distributed Knowledgebases

2016 ◽  
pp. 1572-1591
Author(s):  
Juan Li ◽  
Ranjana Sharma ◽  
Yan Bai
Keyword(s):  
Drug Discovery ◽  
Semantic Web ◽  
Distributed System ◽  
Large Scale ◽  
The Internet ◽  
Full Potential ◽  
Web Data ◽  
Semantic Relationships ◽  
Complex Relationships

Drug discovery is a lengthy, expensive and difficult process. Indentifying and understanding the hidden relationships among drugs, genes, proteins, and diseases will expedite the process of drug discovery. In this paper, we propose an effective methodology to discover drug-related semantic relationships over large-scale distributed web data in medicine, pharmacology and biotechnology. By utilizing semantic web and distributed system technologies, we developed a novel hierarchical knowledge abstraction and an efficient relation discovery protocol. Our approach effectively facilitates the realization of the full potential of harnessing the collective power and utilization of the drug-related knowledge scattered over the Internet.

SWRLx

2018 ◽  
pp. 348-367
Author(s):  
Souad Bouaicha ◽  
Zizette Boufaida
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Object Oriented ◽  
Web Ontology Language ◽  
Rule Engine ◽  
Ontology Language ◽  
New Knowledge ◽  
Semantic Web Rule Language

Although OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) add considerable expressiveness to the Semantic Web, they do have expressive limitations. For some reasoning problems, it is necessary to modify existing knowledge in an ontology. This kind of problem cannot be fully resolved by OWL and SWRL, as they only support monotonic inference. In this paper, the authors propose SWRLx (Extended Semantic Web Rule Language) as an extension to the SWRL rules. The set of rules obtained with SWRLx are posted to the Jess engine using rewrite meta-rules. The reason for this combination is that it allows the inference of new knowledge and storing it in the knowledge base. The authors propose a formalism for SWRLx along with its implementation through an adaptation of different object-oriented techniques. The Jess rule engine is used to transform these techniques to the Jess model. The authors include a demonstration that demonstrates the importance of this kind of reasoning. In order to verify their proposal, they use a case study inherent to interpretation of a preventive medical check-up.

Ontology Augmented Software Engineering

2013 ◽  
pp. 406-413
Author(s):  
Qazi Mudassar Ilyas
Keyword(s):  
Software Engineering ◽  
Semantic Web ◽  
System Integration ◽  
Software Maintenance ◽  
Domain Knowledge ◽  
System Development ◽  
Tracking System ◽  
Software Artifacts ◽  
Natural Choice ◽  
Development Life Cycle

Semantic Web was proposed to make the content machine-understandable by developing ontologies to capture domain knowledge and annotating content with this domain knowledge. Although, the original idea of semantic web was to make content on the World Wide Web machine-understandable, with recent advancements and awareness about these technologies, researchers have applied ontologies in many interesting domains. Many phases in software engineering are dependent on availability of knowledge, and the use of ontologies to capture and process this knowledge is a natural choice. This chapter discusses how ontologies can be used in various stages of the system development life cycle. Ontologies can be used to support requirements engineering phase in identifying and fixing inconsistent, incomplete, and ambiguous requirement. They can also be used to model the requirements and assist in requirements management and validation. During software design and development stages, ontologies can help software engineers in finding suitable components, managing documentation of APIs, and coding support. Ontologies can help in system integration and evolution process by aligning various databases with the help of ontologies capturing knowledge about database schema and aligning them with concepts in ontology. Ontologies can also be used in software maintenance by developing a bug tracking system based upon ontological knowledge of software artifacts and roles of developers involved in software maintenance task.

Approaches for Semantic Association Mining and Hidden Entities Extraction in Knowledge Base

2010 ◽  
pp. 119-141 ◽  
Author(s):  
Thabet Slimani ◽  
Boutheina Ben Yaghlane ◽  
Khaled Mellouli
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Domain Knowledge ◽  
Information And Communications Technology ◽  
Association Mining ◽  
Semantic Association ◽  
Real World Data ◽  
Semantic Associations ◽  
Hyperclique Pattern ◽  
Flow Of Information

Due to the rapidly increasing use of information and communications technology, Semantic Web technology is being increasingly applied in a large spectrum of applications in which domain knowledge is represented by means of an ontology in order to support reasoning performed by a machine. A semantic association (SA) is a set of relationships between two entities in knowledge base represented as graph paths consisting of a sequence of links. Because the number of relationships between entities in a knowledge base might be much greater than the number of entities, it is recommended to develop tools and invent methods to discover new unexpected links and relevant semantic associations in the large store of the preliminary extracted semantic association. Semantic association mining is a rapidly growing field of research, which studies these issues in order to create efficient methods and tools to help us filter the overwhelming flow of information and extract the knowledge that reflect the user need. The authors present, in this work, an approach which allows the extraction of association rules (SWARM: Semantic Web Association Rule Mining) from a structured semantic association store. Then, present a new method which allows the discovery of relevant semantic associations between a preliminary extracted SA and predefined features, specified by user, with the use of Hyperclique Pattern (HP) approach. In addition, the authors present an approach which allows the extraction of hidden entities in knowledge base. The experimental results applied to synthetic and real world data show the benefit of the proposed methods and demonstrate their promising effectiveness.

Referencing Resources through Ontology Evolution

2010 ◽  
pp. 224-244
Author(s):  
Déliar Rogozan ◽  
Gilbert Paquette
Keyword(s):  
Semantic Web ◽  
Domain Knowledge ◽  
Software Agents ◽  
Dynamic Environments ◽  
Ontology Evolution ◽  
Domain Ontologies ◽  
Original Domain ◽  
Fundamental Requirement

Evolution is a fundamental requirement for useful ontologies. Knowledge evolves continuously in all fields of knowledge due to the progress in research and applications. Because they are theories of knowledge in a precise domain, Ontologies need to evolve because the domain has changed, the viewpoint of the domain has changed or because problems in the original domain conceptualization have to be resolved or have been resolved (Noy & Klein, 2003). Moreover, in open and dynamic environments such as the Semantic Web, the ontologies need to evolve because domain knowledge evolves continually (Heflin & Hendler, 2000) or because ontology-oriented software-agents must respond to changes in users’ needs (Stojanovic, Maedche, Stojanovic, & Studer, 2003).

An Overview and Technological Background of Semantic Technologies

2021 ◽  
pp. 1-21
Author(s):  
Reinaldo Padilha França ◽  
Ana Carolina Borges Monteiro ◽  
Rangel Arthur ◽  
Yuzo Iano
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Data Representation ◽  
Current Data ◽  
The Internet ◽  
Semantic Technologies ◽  
Web Based ◽  
Web 3.0 ◽  
Technological Advances ◽  
The Web

The Semantic Web concept is an extension of the web obtained by adding semantics to the current data representation format. It is considered a network of correlating meanings. It is the result of a combination of web-based conceptions and technologies and knowledge representation. Since the internet has gone through many changes and steps in its web versions 1.0, 2.0, and Web 3.0, this last call of smart web, the concept of Web 3.0, is to be associated with the Semantic Web, since technological advances have allowed the internet to be present beyond the devices that were made exactly with the intention of receiving the connection, not limited to computers or smartphones since it has the concept of reading, writing, and execution off-screen, performed by machines. Therefore, this chapter aims to provide an updated review of Semantic Web and its technologies showing its technological origins and approaching its success relationship with a concise bibliographic background, categorizing and synthesizing the potential of technologies.

Non-Monotonic Modeling for Personalized Services Retrieval and Selection

2010 ◽  
Vol 1 (2) ◽  
pp. 55-68 ◽  
Author(s):  
Raymond Y. K. Lau ◽  
Wenping Zhang
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Semantic Web Services ◽  
The Internet ◽  
Electronic Payment ◽  
Uncertainty Reasoning ◽  
Service Information ◽  
Personalized Services ◽  
Core Elements ◽  
Processing Cycle

With growing interest in Semantic Web services and emerging standards, such as OWL, WSMO, and SWSL in particular, the importance of applying logic-based models to develop core elements of the intelligent Semantic Web has been more closely examined. However, little research has been conducted in Semantic Web services on issues of non-mono-tonicity and uncertainty of Web services retrieval and selection. In this paper, the authors propose a non-monotonic modeling and uncertainty reasoning framework to address problems related to adaptive and personalized services retrieval and selection in the context of micro-payment processing of electronic commerce. As intelligent payment service agents are faced with uncertain and incomplete service information available on the Internet, non-monotonic modeling and reasoning provides a robust and powerful framework to enable agents to make service-related decisions quickly and effectively with reference to an electronic payment processing cycle.

Semantic Portals

2011 ◽  
pp. 887-893
Author(s):  
Brooke Abrahams
Keyword(s):  
Semantic Web ◽  
Entry Point ◽  
Level Of Service ◽  
The Internet ◽  
Web Portals ◽  
Information Presentation ◽  
Process Information ◽  
Internet Technologies ◽  
New Approaches ◽  
The Web

Web portals provide an entry point for information presentation and exchange over the Internet for various domains of interest. Current Internet technologies, however, often fail to provide users of Web portals with the type of information or level of service they require. Limitations associated with the Web affect the users of Web portals ability to search, access, extract, interpret, and process information. The Semantic Web (Berners-Lee, Hendler, & Lassila, 2001) enables new approaches to the design of such portals and has the potential of overcoming these limitations by enabling machines to interpret information so that it can be integrated and processed more effectively.

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