scholarly journals Algorithm of Ontology Transformation to Concept Map for Usage in Semantic Web Expert System

2013 ◽  
Vol 14 (1) ◽  
pp. 80-87
Author(s):  
Olegs Verhodubs ◽  
Janis Grundspenkis
Keyword(s):  
Expert System ◽  
Semantic Web ◽  
Knowledge Base ◽  
Concept Map ◽  
Web Ontology Language ◽  
Subsequent Generation ◽  
Ontology Language ◽  
Owl Ontology ◽  
System Knowledge

Abstract The main purpose of this paper is to present an algorithm of OWL (Web Ontology Language) ontology transformation to concept map for subsequent generation of rules and also to evaluate the efficiency of this algorithm. These generated rules are necessary to supplement and even to develop SWES (Semantic Web Expert System) knowledge base. This paper is a continuation of the earlier research of OWL ontology transformation to rules.

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.

scholarly journals RDB2OWL: AN IMPROVED METHOD FOR CONVERTING RELATIONAL DATABASES INTO OWL

2017 ◽  
Vol 7 (2) ◽  
pp. 129
Author(s):  
Phạm Thị Thu Thúy
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Web Ontology Language ◽  
Improved Method ◽  
Ontology Language ◽  
Owl Ontology

Một trong những lợi thế của Semantic Web là để mô tả dữ liệu với một ý nghĩa rõ ràng và liên kết giữa các dữ liệu bằng cách sử dụng ngôn ngữ OWL (Web Ontology Language). Ngày nay hầu hết các dữ liệu được lưu trữ trong cơ sở dữ liệu quan hệ. Để tận dụng lại các dữ liệu này, cần thiết phải có phương pháp chuyển dữ liệu lưu trữ trong cơ sở dữ liệu quan hệ vào định dạng của OWL Ontology. Một số phương pháp đã được đề xuất, tuy nhiên, hầu hết các quy tắc chuyển đổi đã không được hoàn chỉnh. Bài báo này đề xuất một số quy tắc cải thiện trong việc chuyển đổi cơ sở dữ liệu quan hệ sang OWL Ontology. Ngoài ra, tất cả các bước chuyển đổi trong thuật toán RDB2OWL được thực hiện tự động mà không cần bất kỳ sự can thiệp của người dùng.

SWRLx

2016 ◽  
Vol 12 (2) ◽  
pp. 53-69 ◽  
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.

scholarly journals Building an OWL ontology with Xper3

2018 ◽  
Vol 2 ◽  
pp. e25614 ◽  
Author(s):  
Florian Pellen ◽  
Sylvain Bouquin ◽  
Isabelle Mougenot ◽  
Régine Vignes-Lebbe
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Expressive Power ◽  
Knowledge Bases ◽  
User Friendliness ◽  
Standard Format ◽  
Ontology Language ◽  
Closed World ◽  
Web Standards ◽  
Description Framework

Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.

Web Intelligence

Big Data ◽  
2016 ◽  
pp. 711-733 ◽  
Author(s):  
Jafreezal Jaafar ◽  
Kamaluddeen Usman Danyaro ◽  
M. S. Liew
Keyword(s):  
Big Data ◽  
Knowledge Base ◽  
Data Model ◽  
Performance Comparison ◽  
Web Ontology Language ◽  
Web Intelligence ◽  
Knowledge Based ◽  
Ontology Language ◽  
And Performance ◽  
Fuzzy Knowledge

This chapter discusses about the veracity of data. The veracity issue is the challenge of imprecision in big data due to influx of data from diverse sources. To overcome this problem, this chapter proposes a fuzzy knowledge-based framework that will enhance the accessibility of Web data and solve the inconsistency in data model. D2RQ, protégé, and fuzzy Web Ontology Language applications were used for configuration and performance. The chapter also provides the completeness fuzzy knowledge-based algorithm, which was used to determine the robustness and adaptability of the knowledge base. The result shows that the D2RQ is more scalable with respect to performance comparison. Finally, the conclusion and future lines of the research were provided.

Ontology-Based Travel Recommender System

2021 ◽  
pp. 460-476
Author(s):  
Shi Pu ◽  
Isibor Kennedy Ihianle
Keyword(s):  
Recommender Systems ◽  
Recommender System ◽  
Web Ontology Language ◽  
Satisfaction Rate ◽  
Semantic Data ◽  
Ontology Language ◽  
Overall Evaluation ◽  
Owl Ontology ◽  
Travel Recommendation

Recommender systems are designed to suggest information to users according to their preferences. The items could be movies, books, or various kinds of products. Most of the existing recommender systems are based on a database with limited advantages. However, in this chapter, the authors propose a knowledge-driven travel recommender system to integrate semantic data built using web ontology language (OWL) ontology to allow users to find suitable destinations that fulfil users' travel preferences. This work aims to develop a travel recommendation tool and to examine the reliability, the usability of the system, and satisfaction rate of users. They are also able to demonstrate that users can obtain desired results through queries on the ontology-based system. The overall evaluation of the system shows that users are happy and satisfied with the recommendation results.

Semantic Descriptions of Web Services

2011 ◽  
pp. 31-73
Author(s):  
Farshad Hakimpour ◽  
Suo Cong ◽  
Daniela E. Damm
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Emerging Technology ◽  
Semantic Web Services ◽  
Web Ontology Language ◽  
Ontology Language ◽  
Technical Details ◽  
Key Features ◽  
Selection Of

This chapter introduces the emerging technology of Semantic Web services. It concentrates on two dominant specifications in this domain, namely OWL-S (Web ontology language for services) and WSMO (Web services modeling ontology). We briefly introduce Web services and Semantic Web, two main technologies underlying the Semantic Web services technology and then explain most of the key features of this technology together with simplified examples. We discuss three aspects of Semantic Web services: specifications for semantic descriptions of services, intelligent discovery and selection of services using semantic descriptions, and finally, building more complex services by composing existing ones. Our main goal in this chapter is not only to present an abstract view of this technology but also the introduction of the technical details of the two existing specifications.

Construction of XBRL Semantic Metamodel and Knowledge Base Based on Ontology

2014 ◽  
Vol 571-572 ◽  
pp. 1119-1128
Author(s):  
Wen Li Wang ◽  
Min Huang ◽  
Ying Wang
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Financial Reporting ◽  
Semantic Information ◽  
Semantic Web Technologies ◽  
Semantic Level ◽  
Web Technologies ◽  
Translation Mechanism ◽  
Owl Ontology

In order to improve the interoperability of XBRL format financial reporting on the semantic level, a novel XBRL financial reporting metamodel and a fact data semantic metamodel are proposed, which uses the Semantic Web technologies and Ontology theory. Then, a XBRL knowledge base is constructed based on this metamodel .Using the metamodel-based translation mechanism from XBRL to OWL / RDF, all the semantic information in XBRL taxonomy and instance documents is translated into OWL ontology and RDF instance. Finally, a knowledge base covering the semantic information of financial reporting domain is constructed.

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