自组织P2P网络的语义聚类查询算法

P2P网络中参与资源共享的节点日益增多,且呈海量趋势。如何在海量用户海量资源的情况下,查询整个P2P网络中的资源语义分布,计算网络中的所有语义聚类,是一个颇具挑战性的问题。针对这一问题,本文提出了一种面向自组织P2P网络的语义聚类查询算法SCQASPNSR。该算法可高效计算整个P2P网络中的语义聚类,为研究网络中资源语义分布、进行有效的知识发现,提供了有力支持。     

On Capturing Semantics in Ontology Mapping

Semantic interoperability between disparate systems in open, distributed environments has become the quest of many practitioners in a variety of fields. One way to achieve such a goal is through ontology mapping. The perspective users of such technology, however, are faced with a number of challenges including ambiguity of the meaning of mappings, difficulties of capturing semantics, choice of the right ontology mapping tools, verification and validation of results and operationalisation in the beneficiary semantic web application. In this paper we present a formalisation of ontologies and a triangle model for the ontology mapping problems. This formalisation of ontology mapping reflects the engineering steps needed to materialise a versatile mapping system in order to faithfully re-capture the semantics embodied in ontologies which is the fundamental requirements posed by the semantic web environment. We further accommodate this formalisation with a series of specialist algorithms targeting at particular aspects of semantic capturing. Finally, we evaluated the proposed algorithms by way of ontology mapping benchmark tests.     

P2P数据管理系统中数据表的定位

P2P数据管理系统已经成为对等计算领域的研究重点。语义异构是P2P数据管理系统的首要问题。为了解决此问题,在每个数据源节点对共享的数据表的表名和属性名分别定义一系列关键字作为语义映射的媒介,具有相同关键字的异构数据源之间自动建立映射关系。这些关键字就形成了共享数据的外模式。但在节点内部,没有将外模式真正地物化为视图。定义好的关键字使用外模式描述文件分布到整个网络中。在查询的过程中,找到外模式描述文件后,立即将查询请求中的所有别名转换为真实的数据表名和属性名,从而既可以方便地按照任意名字找到需要的数据表,又可以减少数据备份的数量,简化查询算法,提高系统效率。     

一种基于分组的语义对等网络

以语义网络理论为基础,结合GCNET拓扑结构,提出一种基于分组的语义对等网络——Semantic GCNET,充分利用GCNET网络具有小世界特征的优点,确保其搜索限制在与查询主题相关的局部节点子集中,解决其他一些语义对等网络对主题群搜索低效的问题,克服一些语义对等网络仅支持精确匹配查找的缺点。实验结果表明,Semantic GCNET具有高效的语义查询性能和查全率。     

Ontologies are not the Panacea in Data Integration: A Flexible Coordinator to Mediate Context Construction

Shared ontologies describe concepts and relationships to resolve semantic conflicts amongst users accessing multiple autonomous and heterogeneous information sources. We contend that while ontologies are useful in semantic reconciliation, they do not guarantee correct classification of semantic conflicts, nor do they provide the capability to handle evolving semantics or a mechanism to support a dynamic reconciliation process. Their limitations are illustrated through a conceptual analysis of several prominent examples used in heterogeneous database systems and in natural language processing. We view semantic reconciliation as a nonmonotonic query-dependent process that requires flexible interpretation of query context, and as a mechanism to coordinate knowledge elicitation while constructing the query context. We propose a system that is based on these characteristics, namely the SCOPES (Semantic Coordinator Over Parallel Exploration Spaces) system. SCOPES takes advantage of ontologies to constrain exploration of a remote database during the incremental discovery and refinement of the context within which a query can be answered. It uses an Assumption-based Truth Maintenance System (ATMS) to manage the multiple plausible contexts which coexist while the semantic reconciliation process is unfolding, and the Dempster-Shafer (DS) theory of belief to model the likelihood of these plausible contexts.     

基于Super-P2P语义网格的知识共享模型

在语义网格的研究中,如何超越集中式的语义存储,实现更高程度的资源共享,是目前语义网格的研究热点之一。在分析多种P2P结构的基础上,该文Super-P2P结构应用于语义网格,以解决语义网格的语义集中式存储问题。研究了Super-P2P语义网格的资源发现机制以及基于其的知识服务。应用案例分析证明,基于Super-P2P语义网格的知识共享模型可以实现更高程度的资源共享,提供高质量、高可靠性的知识服务。     

Semantic Ontology Mapping for Interoperability of Learning Resource Systems using a rule-based reasoning approach

There is an increasing demand for sharing learning resources between existing learning resource systems to support reusability, exchangeability, and adaptability. The learning resources need to be annotated with ontologies into learning objects that use different metadata standards. These ontologies have introduced the problems of semantic and structural heterogeneity. This research proposes a Semantic Ontology Mapping for Interoperability of Learning Resource Systems. To enable semantic ontology mapping, this research proposes conflict detection and resolution techniques for both semantic and structural conflicts. The Semantic Bridge Ontology has been proposed as a core component for generating mapping rules to reconcile terms defined in local ontologies into terms defined in the target common ontology. This work defines the reasoning rules to classify related learning objects to enhance the powerful deductive reasoning capabilities of the system. As a consequence, ontology-based learning object metadata are generated and used by the semantic query engine to facilitate user queries of learning objects across heterogeneous learning resource systems.     

Deriving similarity for Semantic Web using similarity graph

One important research challenge of current Semantic Web is resolving the interoperability issue across ontologies. The issue is directly related to identifying semantics of resources residing in different domain ontologies. That is, the semantics of a concept in an ontology differs from others according to the modeling style and intuition of the knowledge expert even though they are the same forms of a concept in each respective ontology. In this paper, we propose a similarity measure to resolve the interoperability issue by using a similarity graph. The strong point of this paper is that we provide a precise mapping technique and similarity properties to derive the similarity. The novel contribution of this paper is that we provide a core technique of computing similarity across ontologies of Semantic Web. This research was supported by the MIC (Ministry of Information and Communication), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment).     

Scalable and topology-aware reconciliation on P2P networks

Collaborative applications are characterized by high levels of data sharing. Optimistic replication has been suggested as a mechanism to enable highly concurrent access to the shared data, whilst providing full application-defined consistency guarantees. Nowadays, there are a growing number of emerging cooperative applications adequate for Peer-to-Peer (P2P) networks. However, to enable the deployment of such applications in P2P networks, it is required a mechanism to deal with their high data sharing in dynamic, scalable and available way. Previous work on optimistic replication has mainly concentrated on centralized systems. Centralized approaches are inappropriate for a P2P setting due to their limited availability and vulnerability to failures and partitions from the network. In this paper, we focus on the design of a reconciliation algorithm designed to be deployed in large scale cooperative applications, such as P2P Wiki. The main contribution of this paper is a distributed reconciliation algorithm designed for P2P networks (P2P-reconciler). Other important contributions are: a basic cost model for computing communication costs in a DHT overlay network; a strategy for computing the cost of each reconciliation step taking into account the cost model; and an algorithm that dynamically selects the best nodes for each reconciliation step. Furthermore, since P2P networks are built independently of the underlying topology, which may cause high latencies and large overheads degrading performance, we also propose a topology-aware variant of our P2P-reconciler algorithm and show the important gains on using it. Our P2P-reconciler solution enables high levels of concurrency thanks to semantic reconciliation and yields high availability, excellent scalability, with acceptable performance and limited overhead.     

Semantic web services publication and OCT-based discovery in structured P2P network

Semantic web services (SWS) technology is developed to overcome the shortcomings of traditional standards, such as WSDL and UDDI, and enable maximal automation in all aspects of web service. But great improvement of capability in SWS-based service discovery is still desired. To address this issue, we present a distributed and semantic-matching-based approach for SWS publication and discovery by leveraging structured P2P technology. In this paper, first, we present our service matching rule which focuses on the inputs and outputs of SWS. Then, to realize this rule in open distributed environment and achieve the optimal match between a query and its qualified services, we propose not only a concept of ordered-concept-tree (OCT) to semantically sort the relevant concepts for service matching, but also a method to publish ontologies on structured P2P network to freely share and make full use of the concepts defined in different ontologies for OCT construction. Finally, we present a method for SWS publication on P2P network and an algorithm for service discovery. We also conduct experiments to evaluate our approach and the experimental results demonstrate its scalability, effectiveness, and callback capability to discover semantic web services.     

基于P2P的结构化半分布式语义搜索算法

目前的搜索引擎算法大多是基于关键词搜索,体系上是集中式结构,在安全性和语义性上存在缺陷.基于P2P的结构化半分布式语义搜索算法--DPSS(Distributed P2P Semantic Search),通过研究词与词的关联度,在传统的P2P覆盖语义层,实现语义功能.同时,结合文章距离算法,能够应用在文本分类、文章聚类等领域.     

语义集成中的不确定性本体映射模型

语义Web的高速发展使其具有动态性和异构性特征,解决语义信息的异构性问题成为实现信息集成的关键。本体作为一种语义Web的知识表示形式,增强了Web的语义信息。因此,为了解决语义异构性,实现数据间的互操作,必须建立异构本体间的映射关系。然而,为庞大的异构本体建立完全精确的本体映射是不现实的,本体映射中存在一定的不确定性。提出了一种新型的本体映射框架——语义集成中的不确定性本体映射。从不同方面研究本体特征,集合了多种映射策略,并引入了各映射策略中不确定性匹配的解决方案。实验证明,该方法具有可靠的实验性能,并且具有很好的通用性和可扩展性。     

中文本体映射研究与实现

本体间的异构是语义网建设亟待解决的问题,本体映射则是解决本体异构的有效手段。中文资源是信息网络的重要组成部分,实现中文本体间以及中文与其他本体的映射是实现知识共享重用的一个重要组成部分。本文从元素层的角度对中文本体映射进行了研究,提出利用知网,结合多种技术计算词汇相似度,利用词汇的相似度计算概念匹配的可信度,实现元素层本体映射的算法,并根据此算法实现了ELOMC(Element Level Ontology Matching for Chinese)系统。     

分布非结构化P2P网络资源定位研究

P2P系统是一个分布式系统,其中的资源如何进行定位是一个重要的问题。通过对分布非结构化P2P系统的搜索机制以及现有的改进方法的研究,给出了一种基于语义路由改进算法,并对此算法进行了模拟仿真。     

从ER模式到OWL DL本体的语义保持的翻译

提出了一种从ER模式到OWL DL本体的语义保持的翻译方法.该方法在形式化表示ER模式的基础上,建立ER模式和OWL DL本体之间精确的概念对应,通过一个翻译算法按照一组预定义的映射规则实现模式翻译.理论分析表明,该方法是语义保持的和有效的;算法实现和案例研究进一步证实,完全自动的机器翻译是可实现的.该文方法是原创性的,为Web本体的开发以及数据库和语义Web之间语义互操作的实现开辟了一条有效途径.     

基于机器学习的本体概念相似性研究

现有的知识系统使用的是集中式的、一致性的、可扩充的Ontology库,不同本体间的语义匹配是语义网发展面临的最富挑战性的问题之一。本文针对领域中存在不同的Ontology的问题,讨论了一种基于多策略机器学习的Ontology匹配方法,重点分析了本体概念的相似度计算,并提出了一种相似度测量算法。     

基于语义的p2p路由算法研究综述

路由算法在P2P网路中占有重要的地位,资源的定位、查找均依赖于高效的路由算法。传统的P2P网络采用分布式哈希表来进行路由,是与资源的自然语义内容无关的算法,或者说分布式哈希表破坏了自然语言的语义内容。最近10年以来,语义路由算法在P2P网络中逐渐兴起。随着语义网的提出,本体成为自然语言研究方面的热点。语义覆盖网正是基于本体的知识体系构建的。而随着社交网路的兴起,又提出了语义小世界的概念。LSI、LSH、VSM以及各中聚类算法均在P2P网络的语义路由中得到了广泛的应用。     

语义物联网中一种多领域信息互操作方法

针对当前语义物联网尚未形成一套比较完善、可共享的语义系统,无法支持不同领域资源描述和语义互操作性问题,提出了一个语义物联网中基于多个领域本体及链接开放数据的语义互操作方法。该方法可以半自动化标注新部署的传感器,为传感器数据添加语义,使机器理解数据含义,并对其进行推理;采用本体实体表管理同一领域本体,来规范统一本体;基于链接开放数据获取命名实体相关的语义,对信息进行补充。最后通过具体实例阐述其工作过程,并与其它经典的方法进行比较。结果表明,其可以较好的实现多领域信息的互操作。     

一种双层P2P结构的语义服务发现模型

在开放的Internet环境下,多本体共存是一种必然.同时,集中式的语义服务发现机制是整个面向服务计算的瓶颈,导致系统的可扩展性差.为了支持多本体共存并提高系统的可扩展性,提出一种双层P2P语义服务发现模型.该模型以本体社区为核心,将iVCE(Internet-based virtual computing environment)的核心概念集成到P2P模型中.基于该模型,提出一种分两个阶段、3个步骤的服务发现算法.除了在本体社区内以外,算法还可以实现跨社区的服务发现.在本体社区内,算法首先根据语义相似性选定相应的注册服务器,然后再利用逻辑推理来实施精确的服务匹配.而跨社区的服务发现则按照一定的策略实施.该模型适用于多本体共存的开放环境.实验结果表明,通过合理的参数配置,模型能在查全率和服务发现响应时间之间加以折衷,并取得较好的结果;另外,模型能够在不降低服务查全率的情况下降低注册服务节点的平均负载.