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.     

Bridging the semantic Web and Web 2.0 with Representational State Transfer (REST)

Semantic Web technologies must integrate with Web 2.0 services for both to leverage each others strengths. We argue that the REST-based design methodologies [R.T. Fielding, R.N. Taylor, Principled design of the modern web architecture, ACM Trans. Internet Technol. (TOIT) 2 (2) (2002) 115–150] of the web present the ideal mechanism through which to align the publication of semantic data with the existing web architecture. We present the design and implementation of two solutions that combine REST-based design and RDF [D. Beckett (Ed.), RDF/XML Syntax Specification (Revised), W3C Recommendation, February 10, 2004] data access: one solution for integrating existing web services and one server-side solution for creating RDF REST services. Both of these solutions enable SPARQL [E. Prud’hommeaux, A. Seaborne (Eds.), SPARQL Query Language for RDF, W3C Working Draft, March 26, 2007] to be a unifying data access layer for aligning the Semantic Web and Web 2.0.     

Semantic email: theory and applications

This paper investigates how the vision of the Semantic Web can be carried over to the realm of email. We introduce a general notion of semantic email, in which an email message consists of a structured query or update coupled with corresponding explanatory text. Semantic email opens the door to a wide range of automated, email-mediated applications with formally guaranteed properties. In particular, this paper introduces a broad class of semantic email processes. For example, consider the process of sending an email to a program committee, asking who will attend the PC dinner, automatically collecting the responses, and tallying them up. We define both logical and decision-theoretic models where an email process is modeled as a set of updates to a data set on which we specify goals via certain constraints or utilities. We then describe a set of inference problems that arise while trying to satisfy these goals and analyze their computational tractability. In particular, we show that for the logical model it is possible to automatically infer which email responses are acceptable w.r.t. a set of constraints in polynomial time, and for the decision-theoretic model it is possible to compute the optimal message-handling policy in polynomial time. In addition, we show how to automatically generate explanations for a process's actions, and identify cases where such explanations can be generated in polynomial time. Finally, we discuss our publicly available implementation of semantic email and outline research challenges in this realm.¹     

Ease of interaction plus ease of integration: Combining Web2.0 and the Semantic Web in a reviewing site

Web2.0 has enabled contributions to the Web on an unprecedented scale, through simple interfaces that provide engaging interactions. This wealth of data has spawned countless mashups that integrate heterogenous information, but using techniques that will not scale beyond a handful of sources. In contrast, the Semantic Web provides the key to large-scale data integration, yet still lacks approachable interfaces allowing contributions from non-specialists. In this paper we present Revyu, a reviewing and rating site in the Web2.0 mould that is built on Semantic Web infrastructure and both publishes and consumes linked RDF data. This combination of approaches affords ease of interaction for regular users and ease of integration with external data sources.     

防火墙技术与网络安全

随着网络的迅速发展,如何保护信息的安全成了现在的重点。本文简单介绍了当今流行的防火墙技术,分析了目前防火墙的功能特性。介绍了目前防火墙的优缺点。概括介绍了目前两大流行防火墙 CheckPoint 的状态检测技术(ateful Inspection)和 Web 智能技术(Web Intelligence)对于防火墙的智能防御与 Web 安全保护特点。     

Supporting concurrent ontology development: Framework, algorithms and tool

We propose a novel approach to facilitate the concurrent development of ontologies by different groups of experts. Our approach adapts Concurrent Versioning, a successful paradigm in software development, to allow several developers to make changes concurrently to an ontology. Conflict detection and resolution are based on novel techniques that take into account the structure and semantics of the ontology versions to be reconciled by using precisely-defined notions of structural and semantic differences between ontologies and by extending state-of-the-art ontology debugging and repair techniques. We also present ContentCVS, a system that implements our approach, and a preliminary empirical evaluation which suggests that our approach is both computationally feasible and useful in practice.     

安全的Web服务集成框架分析与设计

提出了一个可扩展的Web服务的安全体系架构模型：SX_RSRPM模型,该模型通过对协议栈进行安全性扩展和增加安全认证角色有效地提高了Web服务的安全度。在基于XML的安全技术、WS_Seclurity协议的分析基础上,提出了Web服务的应用安全层次结构,并在开发OPEN-CLASS平台的过程中形成了一个实用的Web服务应用安全集成方案。     

制造网格资源调度及安全性管理

根据制造网格发展的现状和方向,分析了网格资源调度的主要方法,并对Globus环境下的GSI体系结构做了深入研究,分析讨论了其任务提交执行过程和架构特点,对现有的GSI架构基础做了相关改进,构建了一个满足制造网格下部分特性的安全体系结构M-GSI,实现了实时认证和强授权功能,满足了制造网格部分安全需求。     

Data provenance in SOA: security, reliability, and integrity

Due to the dynamic nature, such as services composition and evaluation, it is critical for a Service-Oriented Architecture (SOA) system to consider its data provenance, which concerns security, reliability, and integrity of data as they are being routed in the system. In a traditional software system, one focuses on the software itself to determine the security, reliability, and integrity of the software. In an SOA system, however, one also needs to consider origins and routes of data and their impact, i.e., data provenance. This paper first analyzes the unique nature and characteristics of data provenance in an SOA system, particularly related to data security, reliability, and integrity. Then it proposes a new framework for data provenance analysis in an SOA system. Finally, this paper uses an example which illustrates these techniques.     

Aggregated search of data and services

From a user perspective, data and services provide a complementary view of an information source: data provide detailed information about specific needs, while services execute processes involving data and returning an informative result as well. For this reason, users need to perform aggregated searches to identify not only relevant data, but also services able to operate on them. At the current state of the art such aggregated search can be only manually performed by expert users, who first identify relevant data, and then identify existing relevant services.     

Scale and performance in semantic storage management of data grids

Data grids are middleware systems that offer secure shared storage of massive scientific datasets over wide area networks. The main challenge in their design is to provide reliable storage, search, and transfer of numerous or large files over geographically dispersed heterogeneous platforms. The Storage Resource Broker (SRB) is an example of a system that provides these services and that has been deployed in multiple high-performance scientific projects during the past few years. In this paper, we take a detailed look at several of its functional features and examine its scalability using synthetic and trace-based workloads. Unlike traditional file systems, SRB uses a commodity database to manage both system- and user-defined metadata. We quantitatively evaluate this decision and draw insightful conclusions about its implications to the system architecture and performance characteristics. We find that the bulk transfer facilities of SRB demonstrate good scalability properties, and we identify the bottleneck resources across different data search and transfer tasks. We examine the sensitivity to several configuration parameters and provide details about how different internal operations contribute to the overall performance.     

Relations between semantic security and anonymity in identity-based encryption

Semantic security and anonymity are the two main properties that an identity-based encryption scheme can satisfy. Such properties can be defined in either an adaptive or a selective scenario, which differ on the moment where the attacker chooses the identity/ies that are the target of the attack. There are well-known separations between selective and adaptive semantic security on the one hand, and between selective and adaptive anonymity on the other hand.In this paper we investigate the relations between these selective and adaptive notions, for identity-based encryption schemes enjoying at the same time some security and anonymity properties. On the negative side, we prove that there is a separation between selective and adaptive anonymity even for schemes which enjoy adaptive semantic security. On the positive side, we prove that selective semantic security and adaptive anonymity imply adaptive semantic security.     

基于云计算的数据安全风险及防范策略探讨

云计算依托计算机网络系统,目前已经成为人们生活的重要部分,随着网络化、虚拟化生活的加速发展,诸如Google、Microsoft、Apple、Amazon、IBM等互联网IT和手机、网络运营商巨头开始重新定位企业发展的战略核心.云计算作为IT商业计算模型,它将计算任务分布在各种类型的广域网络和局域网络组成计算机网络系统,使用户能够借助网络按需获取计算力、存储空间和信息服务.云计算的用户通过PC、手机以及其他终端连接到网络使用云资源;随着云计算的广泛应用,云计算的环境安全环境、数据安全成为突出问题,如何保障云计算的安全成为当前急需解决的问题.本文介绍了云计算相关概念,以及对云计算数据安全风险进行分析,并提出了防范策略.     

西藏高校数字图书馆数据安全现状分析及防护策略

数据安全是图书馆开展各项数字化服务前提和保证,本文通过分析目前西藏高校图书馆数据安全的现状及存在的问题,结合西藏各高校图书馆实际,提出了数据安全的防护策略,希望为西藏高校图书馆数据安全建设抛砖引玉。     

Towards a Machine of a Process (MOP) ontology to facilitate e-commerce of industrial machinery

Adapting to user's requirements is a key factor for enterprise success. Despite the existence of several approaches that point in this direction, simplifying integration and interoperability among users, suppliers and the enterprise during product lifecycle, is still an open issue. Ontologies have been used in some manufacturing applications and they promise to be a valid approach to model manufacturing resources of enterprises (e.g. machinery and raw material). Nevertheless, in this domain, most of the ontologies have been developed following methodologies based on development from scratch, thus ontologies previously developed have been discarded. Such ontological methodologies tend to hold the interoperability issues in some level. In this paper, a method that integrates ontology reuse with ontology validation and learning is presented. An upper (top-level) ontology for manufacturing was used as a reference to evaluate and to improve specific domain ontology. The evaluation procedure was based on the systemic methodology for ontology learning (SMOL). As a result of the application of SMOL, an ontology entitled Machine of a Process (MOP) was developed. The terminology included in MOP was validated by means of a text mining procedure called Term Frequency–Inverse Document Frequency (TF–IDF) which was carried out on documents from the domain in this study. Competency questions were performed on preexisting domain ontologies and MOP, proving that this new ontology has a performance better than the domain ontologies used as seed.     

基于SOA的企业人力资源管理系统体系结构框架与应用

针对企业人力资源管理中存在的人工管理效率低下、绩效评估手段单一及管理信息系统中的“信息孤岛”、系统平台异构、扩展能力差等问题,在Web服务和SOA定义的基础上,设计了基于SOA的企业人力资源管理系统体系结构框架的物理视图和逻辑视图,给出了各视图的组成部分和实现策略,同时将Ajax技术引入到系统设计中.最后将系统体系结构框架的物理视图和逻辑视图应用到某军工企业人力资源信息管理系统的开发过程中,验证所提体系结构框架视图的可行性和有效性.目前该系统运行稳定,用户反应良好.     

Evolving meta-ensemble of classifiers for handling incomplete and unbalanced datasets in the cyber security domain

Cyber security classification algorithms usually operate with datasets presenting many missing features and strongly unbalanced classes. In order to cope with these issues, we designed a distributed genetic programming (GP) framework, named CAGE-MetaCombiner, which adopts a meta-ensemble model to operate efficiently with missing data. Each ensemble evolves a function for combining the classifiers, which does not need of any extra phase of training on the original data. Therefore, in the case of changes in the data, the function can be recomputed in an incremental way, with a moderate computational effort; this aspect together with the advantages of running on parallel/distributed architectures makes the algorithm suitable to operate with the real time constraints typical of a cyber security problem. In addition, an important cyber security problem that concerns the classification of the users or the employers of an e-payment system is illustrated, in order to show the relevance of the case in which entire sources of data or groups of features are missing. Finally, the capacity of approach in handling groups of missing features and unbalanced datasets is validated on many artificial datasets and on two real datasets and it is compared with some similar approaches.     

Piazza: mediation and integration infrastructure for Semantic Web data

The Semantic Web envisions a World Wide Web in which data is described with rich semantics and applications can pose complex queries. To this point, researchers have defined new languages for specifying meanings for concepts and developed techniques for reasoning about them, using RDF as the data model. To flourish, the Semantic Web needs to provide interoperability—both between sites with different terminologies and with existing data and the applications operating on them. To achieve this, we are faced with two problems. First, most of the world’s data is available not in RDF but in XML; XML and the applications consuming it rely not only on the domain structure of the data, but also on its document structure. Hence, to provide interoperability between such sources, we must map between both their domain structures and their document structures. Second, data management practitioners often prefer to exchange data through local point-to-point data translations, rather than mapping to common mediated schemas or ontologies.This paper describes the Piazza system, which addresses these challenges. Piazza offers a language for mediating between data sources on the Semantic Web, and it maps both the domain structure and document structure. Piazza also enables interoperation of XML data with RDF data that is accompanied by rich OWL ontologies. Mappings in Piazza are provided at a local scale between small sets of nodes, and our query answering algorithm is able to chain sets mappings together to obtain relevant data from across the Piazza network. We also describe an implemented scenario in Piazza and the lessons we learned from it.