Searching and browsing Linked Data with SWSE: The Semantic Web Search Engine

In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data – loosely also known as Linked Data – which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web – in terms of scale, unreliability, inconsistency and noise – are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.     

Using the Semantic Web for linking and reusing data across Web 2.0 communities

Large volumes of content (bookmarks, reviews, videos, etc.) are currently being created on the “Social Web”, i.e. on Web 2.0 community sites, and this content is being annotated and commented upon. The ability to view an individual's entire contribution to the Social Web would be an interesting and valuable service, particularly important as social networks are often being formed through created content and things that people have in common (“object-centred sociality”). SIOC is a Semantic Web research project that aims to describe online communities on the Social Web. This paper describes how SIOC and the Semantic Web can enable linking and reuse scenarios of data from Web 2.0 community sites, and introduces a SIOC Types module to further specify the type of content items and act as a “glue” between user posts and the content items created and annotated by users.     

语义Web

介绍了语义Web的概念有本体模型在其中的运用，比较了XML/XML Schema和RDF/RDF Schema在语义表示方面的使用，提出RDF（S）更适合于语义Web；最后讨论了扩展RDF开发语义Web应用所应该注意的问题。     

基于语义的Web挖掘

基于语义的Web挖掘是使用从现有Web数据中抽取的语义或直接使用Web数据中已有的语义结构来帮助Web挖掘。它有效地结合了语义网和Web挖掘两个领域的研究成果,既可以通过开发新的语义结构来帮助Web挖掘,又可以利用挖掘结果促进语义网的创建。本文介绍了基于语义的Web挖掘的基本思想和研究现状,分析了语义网和Web挖掘相结合的优势,并详细论述了国际上关于利用数据挖掘技术创建语义网,利用语义挖掘Web数据和直接挖掘语义网三个方面的研究工作。     

Web服务语义描述的架构

介绍了语义网在Web Service中的应用。在介绍语义网体系结构的基础上,讨论了语义网核心层XML层、RDF层、ONTOLOGY层的前相关技术,最后,就语义网的应用与当前Web Service中的一些应用技术作了简要比较。     

利用语义进行Web结构挖掘

本文论述了利用语义挖掘Web结构、Web使用挖掘进行了基于语义挖掘方法的探讨，并对PageRank算法进行了分析，针对该算法的不足之处进行了改进。     

利用语义进行Web结构挖掘

本文论述了利用语义挖掘Web结构、Web使用挖掘进行了基于语义挖掘方法的探讨,并对PageRank算法进行了分析,针对该算法的不足之处进行了改进。     

语义Web的现状与发展趋势

语义Web是当前Web技术的扩展,是第三代Web.本文阐述了语义Web的概念,探讨了RDF技术及其特点,描述了语义Web的发展趋势.     

一个语义Web构架及其实现

语义Web是国际互联网组织W3C制定的关于未来Web的一个长远蓝图,近两年发展异常迅猛,并显示出诱人的应用前景。该文在概述语义Web基本技术的基础上,设计了一个面向企业门户网站的语义Web体系结构;提出了页面代理的概念及其作用与功能结构;设计了语义Web查询语言CDQL,该语言在跨信息源查询、约束表示等方面扩充了DQL查询语言。     

The two cultures: Mashing up Web 2.0 and the Semantic Web

A common perception is that there are two competing visions for the future evolution of the Web: the Semantic Web and Web 2.0. A closer look, though, reveals that the core technologies and concerns of these two approaches are complementary and that each field can and must draw from the other’s strengths. We believe that future Web applications will retain the Web 2.0 focus on community and usability, while drawing on Semantic Web infrastructure to facilitate mashup-like information sharing. However, there are several open issues that must be addressed before such applications can become commonplace. In this paper, we outline a semantic weblogs scenario that illustrates the potential for combining Web 2.0 and Semantic Web technologies, while highlighting the unresolved issues that impede its realization. Nevertheless, we believe that the scenario can be realized in the short-term. We point to recent progress made in resolving each of the issues as well as future research directions for each of the communities.     

Summarizing Vocabularies in the Global Semantic Web

In the Semantic Web, vocabularies are defined and shared among knowledge workers to describe linked data for scientific, industrial or daily life usage. With the rapid growth of online vocabularies, there is an emergent need for approaches helping users understand vocabularies quickly. In this paper, we study the summarization of vocabularies to help users understand vocabularies. Vocabulary summarization is based on the structural analysis and pragmatics statistics in the global Semantic Web. Local Bipa...     

基于RDF4S语义服务描述模型的服务资源搜索框架

语义服务资源搜索是一个满足服务请求者快速、便捷地定位可用语义服务资源的过程。一个高效、精确的基于语义的语义服务资源搜索框架和经过精心设计并实现的搜索工具是语义服务框架中的一个必要组件。提出一种基于RDF4S语义服务描述模型的服务资源搜索框架,详细说明了该搜索框架的结构。搜索框架根据RDF4S语义服务描述模型的QoS、执行、功能和接口四种语义标注元素类型,分别采用不同的搜索匹配策略,可以很大程度上提高搜索的效率和精度。     

基于本体的语义Web研究

语义Web与本体的关系极为特殊,本体在语义Web本身的体系结构中扮演着极为重要的角色,同时,位于语义Web体系结构的其它层的XML、RDF(S)等与本体也有着千丝万缕的联系。为阐述两者的关系,探讨基于本体的语义Web的特点及应用,介绍了本体和语义Web的产生和发展,在此基础上对基于本体的语义Web进行研究,重点分析了本体在描述语义方面弥补了XML、RDF(S)等的不足,并结合Web服务检索的实例介绍了本体在Web服务上的应用。     

A comparison of two modelling paradigms in the Semantic Web

Classical logics and Datalog-related logics have both been proposed as underlying formalisms for conceptual modelling in the context of the Semantic Web. Although these two different formalism groups have some commonalities, and look similar in the context of expressively impoverished languages like RDF, their differences become apparent at more expressive language levels. After considering some of these differences, we argue that, although some of the characteristics of Datalog have their utility, the open environment of the Semantic Web is better served by standard logics.     

语义传感器Web中的数据管理技术研究

语义传感器Web是由传感器网络技术、分布式计算技术、数据库管理技术和语义Web技术整合发展而来的.语义传感器Web能够感知、收集、整合信息,抽取新的知识并为感知器提供增强语义,因此能对环境的变化有更智能的感知,用户可以通过访问Web获取这些信息.作为计算机科学中一个新的研究领域,它有着广阔的应用前景,引起了工业界和学术界浓厚的兴趣.介绍了语义传感器Web的基本概念、特点,并着重讨论了语义传感器Web数据管理中所存在的研究问题、研究现状和研究成果.     

语义Web的标记语言和体系结构

当前WWW上的信息主要是为人类阅读而设计的，而语义Web试图将WWW上的海量信息以一种机器可理解的方式组织起来，提供数据的语义关系的表达手段，以满足日益增加Web应用对数据互操作性的要求，XML提供了对数据表达的语法的统一描述，RDF和RDF Schema提供了对数据语义的表达手段，本体论（Ontology)是关于领域内共享概念的形式化的规格说明，在语义Web中起重要作用，本体论语言形成关于本体的逻辑描述，这样从下到上形成了语义Web的层次体系结构。     

语义Web中几种语义描述语言的分析比较

介绍了语义Web的概念、产生的背景、革命化的意义,并讨论RDF、RDFS、OIL、DAML-O的语义表示特征以及它们在语义Web中所发挥的重大作用,并举出例子来说明这几种语义描述语言在语义Web中的应用,同时深入分析比较了它们的语义表示能力。     

RDF数据浏览的研究综述

随着语义网的快速发展,目前Web上语义网数据已经达到相当的规模,成为重要的信息和知识来源.因此,RDF数据浏览的研究开始得到广泛关注.通过对比传统Web信息浏览和RDF数据浏览两个问题,指出RDF数据浏览的5个重要问题:确定浏览子图的模式、数据的收集、大规模数据的处理、数据的组织方式以及数据的呈现方式.基于这些挑战,我们调研了多个系统和不同的解决方案.最后,总结了目前的研究现况,讨论存在的挑战,并提出未来的研究方向.     

基于语义的大型人才库检索方法研究

高效率、高质量地进行人才库检索,对于我国的大型企业集团,尤其是水利水电施工企业集团来说意义重大。传统的分类目录和关键词查询方法,不能很好地满足企业的要求。该文采用语义Web中的相关技术,使用RDF语言描述人才库系统中的本体,并将用户的查询要求转化为语义信息,结合匹配度计算模型检索所需的人才,提出了一种基于本体的对大型人才库进行语义检索的方法,并举例说明了该方法的应用。     

一种简历语义搜索系统的实现方法

政府与企事业单位的人事部门通常面临着如何从大量简历中筛选出合适人选的问题。一些业务部门对人才的需求通常只能表达为标签,比如“具有丰富搜索引擎开发经验”、“985高校毕业”等,这些需求不能通过SQL查询或关键词搜索来实现。为了解决这个问题,提出一种基于语义网的简历搜索方法。通过领域知识库辅助信息提取的方法,对简历信息进行语义分析和标签的自动生成。此外,在大规模人员情况下,提出了多层次缓存的方法, 极大提高 了性能。将该方法应用于某 机构 一万人员简历的筛选,实验结果表明了其有效性。