面向模块重用的描述逻辑()本地性规则研究

可重用本体模块的抽取是本体重用的一个关键环节.与传统工程应用中使用的基于本体层次的结构化方法抽取本体模块相比,使用逻辑的方法能充分利用本体提供的语义信息,抽取的本体模块更具完整性和正确性.在研究保守扩展的本体模块理论基础上,根据Grau B C提出的()本地性规则,提出并证明了描述逻辑()对应的语义本地性规则和句法本地性规则,为基于该规则抽取可重用本体模块提供了理论基础.     

基于本体增强语义规则的复杂配电网安全作业控制研究与实现

提出一种基于网络本体语言(OWL)和语义网规则语言(SWRL)的复杂配电网安全作业控制方法。系统基于网络本体语言建立一个可共享、可重用、可扩展的配网安全作业领域本体;将配电网安全防误规则转换成由语义网规则语言表达的推理规则;整合SWRL推理规则与Racer推理机进行推理。系统将电力安全防误规则转换成SWRL形成面向电力的语义网规则语言e-SWRL。实验验证了基于OWL和SWRL的电力安全防误推理方法的有效性与正确性。     

基于?-Connections的旅游领域本体构建

针对传统本体构建方法的局限性,提出一种基于?-Connections理论构建旅游领域模块化本体库的方法,基于改进的Tableau算法,利用Pellet推理机实现对多个本体的联合推理。实验结果证明,该模块化构建方法可以有效降低本体构建的复杂度,有利于本体的维护和更新,提高本体重用模块抽取效率。     

基于ε-Connections的旅游领域本体构建

针对传统本体构建方法的局限性,提出一种基于ε-Connections 理论构建旅游领域模块化本体库的方法,基于改进的Tableau 算法,利用Pellet 推理机实现对多个本体的联合推理.实验结果证明,该模块化构建方法可以有效降低本体构建的复杂度,有利于本体的维护和更新,提高本体重用模块抽取效率.     

基于本体的领域知识重用方法研究*

由于已有知识表示和本体知识表示并不在同一逻辑体系基础上,从知识表示层面提出了一种基于知识等价映射的知识重用方法解决对已有异构知识的重用问题。通过语义等价提取、在本体指导下的一致性处理以及语义映射解决了本体构建过程中对已有知识的自动重用问题。实验表明,该方法易于实现且具有较高的精确性、可行性和有效性。     

利用启发式数据分发策略求解全比较问题

为在全比较(ATAC)问题的分布式计算中达到较高的性能,提出一种基于任务驱动启发式的数据分发策略,充分考虑分布式环境中的存储使用、数据本地性和负载平衡.提出两个分发数据的启发式规则;根据相关约束条件和任务需求,所有的数据项均可在本地进行处理,使对于所有计算任务均具备良好的数据本地性.实验结果表明,对于64个节点的集群,...     

基于本体的物流行业知识库的研究*

构建了基于本体的物流行业信息化知识库。应用语义Web和Web服务技术研究物流知识资源,设计了物流领域本体,实现了文本摘要、规则抽取、本体整合等关键功能,解决物流系统中语义和重用问题,提高了物流企业的知识共享和协作能力。这不仅为物流行业信息化奠定了坚实基础,而且为知识库的复用创造了条件。     

基于OWL描述本体的语义信息抽取

文中描述了一种基于OWL本体抽取出可以被语义Web Agent理解的语义数据的方法,在抽取过程中先将OWL本体模型转换成OSM本体,然后生成抽取规则,并进一步完善本体,最后将抽取出的数据加上语义标记,转换成语义WebAgent可以接收的RDF格式,从而可以促进语义Web的发展。     

Hadoop集群环境下集成抢占式调度策略的本地性调度算法设计

在Hadoop集群环境下本地性调度算法是提高数据本地性的算法。本地性调度算法的调度策略的本质是提高数据本地性,减少网络传输开销,避免阻塞。但是由于Map任务的完成时间不同,Reduce任务存在的等待现象影响了作业的平均完成时间,使得作业的完成时间增加,进而引起系统的性能参数不佳。因此提出在保留原算法数据本地性要求的基础上集成可抢占式的调度方法。在Reduce任务等待时,挂起该任务并释放资源给其他Map任务,当Map任务完成到一定程度后,重新调度Reduce任务。基于上述调度策略设计了集成抢占式策略的本地性调度。为了对改进的算法进行验证,通过实验对本地性调度算法和集成抢占式本地性调度算法进行比较。实验结果表明,在相同数据上,集成抢占式本地性调度算法的平均完成时间有明显的降低。     

基于OWL描述本体的语义信息抽取

文中描述了一种基于OWL本体抽取出可以被语义Web Agent理解的语义数据的方法，在抽取过程中先将OWL本体模型转换成OSM本体，然后生成抽取规则，并进一步完善本体，最后将抽取出的数据加上语义标记，转换成语义WebAgent可以接收的RDF格式，从而可以促进语义Web的发展。     

Survey of modular ontology techniques and their applications in the biomedical domain

In the past several years, various ontologies and terminologies such as the Gene Ontology have been developed to enable interoperability across multiple diverse medical information systems. They provide a standard way of representing terms and concepts thereby supporting easy transmission and interpretation of data for various applications. However, with their growing utilization, not only has the number of available ontologies increased considerably, but they are also becoming larger and more complex to manage. Toward this end, a growing body of work is emerging in the area of modular ontologies where the emphasis is on either extracting and managing "modules" of an ontology relevant to a particular application scenario (ontology decomposition) or developing them independently and integrating into a larger ontology (ontology composition). In this paper, we investigate state-of-the-art approaches in modular ontologies focusing on techniques that are based on rigorous logical formalisms as well as well-studied graph theories. We analyze and compare how such approaches can be leveraged in developing tools and applications in the biomedical domain. We conclude by highlighting some of the limitations of the modular ontology formalisms and put forward additional requirements to steer their future development.     

A Rule-Based Object-Oriented OWL Reasoner

In this paper, we describe O-DEVICE, a memory-based knowledge-based system for reasoning and querying OWL ontologies by implementing RDF/OWL entailments in the form of production rules in order to apply the formal semantics of the language. Our approach is based on a transformation procedure of OWL ontologies into an object-oriented schema and the application of inference production rules over the generated objects in order to implement the various semantics of OWL. In order to enhance the performance of the system, we introduce a dynamic approach of generating production rules for ABOX reasoning and an incremental approach of loading ontologies. O-DEVICE is built over the CLIPS production rule system, using the object-oriented language COOL to model and handle ontology concepts and RDF resources. One of the contributions of our work is that we enable a well-known and efficient production rule system to handle OWL ontologies. We argue that although native OWL rule reasoners may process ontology information faster, they lack some of the key features that rule systems offer, such as the efficient manipulation of the information through complex rule programs. We present a comparison of our system with other OWL reasoners, showing that O-DEVICE can constitute a practical rule environment for ontology manipulation.     

Ontology Integration: Approaches and Challenging Issues

In recent years, the decentralized development of ontologies has led to the generation of multiple ontologies of overlapping knowledge. This heterogeneity problem can be tackled by integrating existing ontologies to build a single coherent one. Ontology integration has been investigated during the last two decades, but it is still a challenging task. In this article, we provide a comprehensive survey of all ontology integration aspects. We discuss related notions and scrutinize existing techniques and literature approaches. We also detail the role of ontology matching in the ontology integration process. Indeed, the ontology community has adopted the splitting of the ontology integration problem into matching, merging and repairing sub-tasks, where matching is a necessary preceding step for merging, and repairing can be included in the matching process or performed separately. Ontology matching and merging systems have become quite proficient, however the trickiest part lies in the repairing step. We also focus on the case of a holistic integration of multiple heterogeneous ontologies, which needs further exploration. Finally, we investigate challenges, open issues, and future directions of the ontology integration and matching areas.     

领域本体建模方法研究

介绍了本体的建模准则,详细分析了现有的本体建模方法,在现有的领域本体构建模式的基础上,通过借鉴其它本体的建立模式,提出了一种新的领域本体建模方法.该方法具有很强的逻辑性和可操作性,可被一些领域本体在建立时采用,所述方法用于构建高校教师本体过程中时效果非常好,体现出了该方法符合人类思维和高度可操作性的特点.     

本体相似度研究

不同本体之间的交互成为语义Web的首要任务,其中本体相似度计算是本体映射的关健环节。在以往的研究中,本体相似度计算通常专注于模式及其结构的匹配。目前研究朝着进一步考虑本体内部语义信息方向努力。本文描述了语义相似度栈的各个层次,依据各个层次的语义特征对目前本体相似度方法进行分类,并对每种方法进行了详细描述。最后对现有一些主要的本体间相似度计算方法进行归纳总结。这项研究工作将为人们提出新的相似度方法或者组合的计算方法作一个参考。     

A comprehensive framework for the evaluation of ontology modularization

The Semantic Web and ontologies have received increased attention in recent years. The delivery of well-designed ontologies enhances the effect of Semantic Web services, but building ontologies from scratch requires considerable time and effort. Modularizing ontologies and integrating ontology modules to a given context help users effectively develop ontologies and revitalize ontology dissemination. Therefore, various tools for modularizing ontologies have been developed. However, selecting an appropriate tool to fit a given context is difficult because the assumptions for the approaches greatly vary. Therefore, a suitable framework is required to compare and help screen the most suitable modularization tool.In this research, we propose a new evaluation framework for selecting an appropriate ontology modularization tool. We present three aspects of tool evaluation as the main dimensions for the assessment of modularization tools: tool performance, data performance, and usability.This study provides an implicit evaluation and an empirical analysis of three modularization tools. It also provides an evaluation method for ontology modularization, enabling ontology engineers to compare different modularization tools and easily choose an appropriate one for the production of qualifying ontology modules.The experimental results indicate that the proposed evaluation criteria for ontology modularization tools are valid and effective. This research provides a useful method for assessing and selecting ontology modularization tools. Modularization performance, data performance, and usability are the three modularization aspects designed and applied to the context of ontology. We provide a new focus on the comprehensive framework to evaluate the performance and usability of ontology modularization tools. The proposed framework should be of value to both ontology engineers, who are interested in ontology modularization, and to practitioners, who need information on how to evaluate and select a specific type of ontology tool in accordance with the requirements of the individual environment.