Ontology and metadata for online learning resource repository management based on semantic web

An ontology and metadata for online learning resource repository management is constructed. First, based on the analysis of the use-case diagram, the upper ontology is illustrated which includes resource library ontology and user ontology, and evaluated from its function and implementation; then the corresponding class diagram, resource description framework （RDF） schema and extensible markup language （XML） schema are given. Secondly, the metadata for online learning resource repository management is proposed based on the Dublin Core Metadata Initiative and the IEEE Learning Technologies Standards Committee Learning Object Metadata Working Group. Finally, the inference instance is shown, which proves the validity of ontology and metadata in online learning resource repository management.

Efficient semantic web service matching using common ontology

To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.

Evaluation of Multistrategy Classifiers for Heterogeneous Ontology Matching On the Semantic Web

On the semantic web, data interoperability and ontology heterogeneity are becoming ever more important issues. To resolve these problems, multiple classification methods can be used to learn the matching between ontologies. The paper uses the general statistic classification method to discover category features in data instances and use the first-order learning algorithm FOIL to exploit the semantic relations among data instances. When using multistrategy learning approach, a central problem is the evaluation of multistrategy classifiers. The goal and the conditions of using multistrategy classifiers within ontology matching are different from the ones for general text classification. This paper describes the combination rule of multiple classifiers called the Best Outstanding Champion, which is suitable for heterogeneous ontology mapping. On the prediction results of individual methods, the method can well accumulate the correct matching of alone classifier. The experiments show that the approach achieves high accuracy on real-world domain.

Ontology在Semantic Web Services中的应用综述

介绍了Web Services的基本原理和Ontology的基本概念。基于这两种技术的结合,简单描述了多种基于本体的Web语言的发展,并重点阐述其中的OWL语言及其在Web Services中应用OWL-S的主要内容。最后介绍本体在语义web服务中的一些拓展性的应用。

Knowledge Representation and Semantic Inference of Process Based on Ontology and Semantic Web Rule Language

The process inference cannot be achieved effectively by the traditional expert system,while the ontology and semantic technology could provide better solution to the knowledge acquisition and intelligent inference of expert system.The application mode of ontology and semantic technology on the process parameters recommendation are mainly investigated.Firstly,the content about ontology,semantic web rule language(SWRL)rules and the relative inference engine are introduced.Then,the inference method about process based on ontology technology and the SWRL rule is proposed.The construction method of process ontology base and the writing criterion of SWRL rule are described later.Finally,the results of inference are obtained.The mode raised could offer the reference to the construction of process knowledge base as well as the expert system's reusable process rule library.

本体（Ontology）与语义网（Semantic Web）

概述了本体的概念、原理、建构方法与应用前景，还介绍了语义网的涵义、体系结构及其发展趋势。参考文献7。

Thesaurus-based approach for building domain ontology with a case study of military aircraft prototype ontology construction

To alleviate the amount of work involved in constructing a domain ontology, starting with the base of an existing terminological-rich thesaurus is better than starting from scratch. With a case study of reengineering the Defense Science and Technology Thesaurus into a prototype military aircraft ontology, a four-phase thesaurus-based methodology is introduced and investigated, which consists of identifying the application purpose, overall design, designing in detail and evaluation. Designing in detail is the core step, converting the terms and semantic relationships of the thesaurus into an ontology and supplementing richer semantic relationships. The resulting prototype ontology includes 87 concepts and 34 relationships, and can be extended and scaled up to a full-fledged domain ontology in the future. Eight universal genres of relationships of this ontology are preliminarily summarized and analyzed, including equivalent relationships, approximate relationships, generic/abstract relationships, part/whole relationships, cause/effect relationships, entity/location relationships etc., and the normalization of semantic relationships is critical to the merging and reusing of follow-up multiple ontologies.

Rules-based object-relational databases ontology construction

To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

Description logics for fuzzy ontologies on semantic web

To enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web, a new fuzzy extension of description logics called the fuzzy description logics with comparison expressions （FCDLs） is presented. The syntax and semantics of FCDLs are formally defined, and the forms of axioms and assertions in FCDLs knowledge bases are specified. FCDLs combine both fuzzy concepts from the fuzzy description logics （FDLs） and cut concepts from the extended fuzzy description logics （EFDLs） in the same theory. Furthermore, cut concepts are extended into comparison cut concepts in FCDLs to represent comparison expressions between fuzzy membership degrees, which are often used in practice but not supported by the other fuzzy extensions of description logics. FCDLs have more expressive power than FDLs and EFDLs, and are able to represent expressive fuzzy knowledge and to perform reasoning tasks based on them. Therefore, FCDLs can enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web.

Novel method for searching ontologies on semantic web

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.

Semantic web-based networked manufacturing knowledge retrieval system

To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.

Semantic Web研究综述

近年来 ,SemanticWeb逐渐成为WWW领域的研究热点以及智能化网络服务和应用开发中的关键技术之一。归纳了Se manticWeb技术的研究背景和主要发展历史。在分析了典型的SemanticWeb概念后 ,给出了SemanticWeb的定义。通过讨论SemanticWeb构想的层次框架模型 ,指出了各个层次扮演的角色 ,并着重分析了SemanticWeb的重要研究领域 ,指出了它们在SemanticWeb构架中的核心作用。通过分析SemanticWeb的应用领域和相关开发工具以及面临的问题和挑战 ,指明了SemanticWeb研究和实践的方向。作为总结 ,给出了SemanticWeb领域下一步的研究趋势。

Semantic Web与基于语义的网络信息检索

本文描述网络环境语义检索的需求 ,分析SemanticWeb的组成框架 ,探讨概念集 (ontologies)及其定义和标记语言 ,并介绍基于概念集的信息资源语义标注和语义推理基本过程。

Semantic Web、Agent和网络虚拟社会

This paper tries to discuss one realizable mode of SW(Semantic Web). It is called NVS(Network-Virtual Society). SW is regarded as the next-generation Web. By adding semantics into Web,SW provides interoperability between applications and facilities to enable automated processing of Web resources. Agent will be the executer in the automated process. After analyzing relational theories and technologies, we put forward the concept and mode of NVS,and gives our reason.

World-Wide Semantic Web of Agriculture Knowledge

The rapid increase in the publication of knowledge bases as linked open data （LOD） warrants serious consideration from all concerned, as this phenomenon will potentially scale exponentially. This paper will briefly describe the evolution of the LOD, the emerging world-wide semantic web （WWSW）, and explore the scalability and performance features Of the service oriented architecture that forms the foundation of the semantic technology platform developed at MIMOS Bhd., for addressing the challenges posed by the intelligent future internet. This paper＂ concludes with a review of the current status of the agriculture linked open data.

信息服务的趋势:Semantic WEB

Web 发展造成了“信息爆炸”和“知识贫乏”的矛盾,基于 XML 和 RDF 发展的语义网是解决这一问题的关键。变“机器可读”为“机器可理解”是语义网的目标,信息服务可以应用语义网的模式和成果,提高搜索的准确率,提供高相关度的个性化服务,构建全新的数字图书馆门户。

An Automatically Filtering Blacklist Model of Social Network Based on Semantic Web

According to the features of the semantic web technology,it is very suitable to solve the security issue of the current social network environment.Firstly,in this paper,it extends the existing ontology model of the social network with some relevant classes,and introduces a brand new ontology which is used to represent the malicious information.After introducing these models,a method of identifying the malicious message is raised.Finally,the experiments and simulations analyze the feasibility of the whole system.The results validate that the malicious users can be automatically filtered,and some worthy digital evidence can be effectively provided to forensic investigators.

Machine Learning Meets the Semantic Web

Remarkable progress in research has shown the efficiency of Knowledge Graphs(KGs)in extracting valuable external knowledge in various domains.A Knowledge Graph(KG)can illustrate high-order relations that connect two objects with one or multiple related attributes.The emerging Graph Neural Networks(GNN)can extract both object characteristics and relations from KGs.This paper presents how Machine Learning(ML)meets the Semantic Web and how KGs are related to Neural Networks and Deep Learning.The paper also highlights important aspects of this area of research,discussing open issues such as the bias hidden in KGs at different levels of graph representation。

Semantic analysis approach for construction of OWL ontology

A semantic analysis approach is proposed, by which semantic relationships between concepts are identified and defined, and then mapped or transformed to OWL （web ontology language） ontology. The most common abstractions （namely, inclusion, aggregation and association） and their implication in ontology are discussed; then the OWL implementation for three abstractions are analyzed and illustrated. Taxonomies, constraints on properties for each class, and the relations between taxonomies in OWL ontology are established after all the semantic relationships are identified and described. This research is the basis for the development of the ontology conceptual model （OCM） and the mapping from OCM to OWL ontology.