Piggy Bank: Experience the Semantic Web inside your web browser

The Semantic Web Initiative envisions a Web wherein information is offered free of presentation, allowing more effective exchange and mixing across web sites and across web pages. But without substantial Semantic Web content, few tools will be written to consume it; without many such tools, there is little appeal to publish Semantic Web content.To break this chicken-and-egg problem, thus enabling more flexible information access, we have created a web browser extension called Piggy Bank that lets users make use of Semantic Web content within Web content as users browse the Web. Wherever Semantic Web content is not available, Piggy Bank can invoke screenscrapers to re-structure information within web pages into Semantic Web format. Through the use of Semantic Web technologies, Piggy Bank provides direct, immediate benefits to users in their use of the existing Web. Thus, the existence of even just a few Semantic Web-enabled sites or a few scrapers already benefits users. Piggy Bank thereby offers an easy, incremental upgrade path to users without requiring a wholesale adoption of the Semantic Web's vision.To further improve this Semantic Web experience, we have created Semantic Bank, a web server application that lets Piggy Bank users share the Semantic Web information they have collected, enabling collaborative efforts to build sophisticated Semantic Web information repositories through simple, everyday's use of Piggy Bank.     

Editorial: Introduction to Web Information Systems Engineering

With the recent advances in the World Wide Web development, more and more users have access to web information, and more and more information providers are able to put information of various types on the web. The web has now become one of the most important Internet information systems for various professionals and users. However, owing to the huge amount of information of various types available and various users on the Internet and Web, efficient query and information retrieval as well as the management of Internet information have become a challenging and difficult task. Therefore, systematic research on the design, implementation, and management of Internet and web-based information systems has been increasingly attractive and important. The Web Information Systems Engineering (WISE) Conference Series (see http://www.i-wise.org) has emerged since 2000 as an excellent forum for researchers, professionals, and industrial practitioners to share their rapidly developing knowledge and report on new advances in web-based information systems.     

Measuring task-specific perceptions of the world wide web

This paper describes the development of multi-item scales for measuring user perceptions of the ease-of-use and usefulness of the Web (hereafter web), incorporating a system task focus into the scales dimensional structure (e.g. how easy or useful the web is for information search, communication and or purchasing). The items are tested on 2077 web users recruited using a web survey, revealing four factors for each scale. Perceived ease-of-web use consists of learning, search and find, transaction and communication ease, and perceived web usefulness consists of communication, purchase, information search and acquisition, and access to quality products and information. A regression analysis on web usage frequency shows how easy users find it to learn how to use the web and how useful the web is for purchasing are the best predictors of how frequently they will use the web. These results highlight the importance of training users how to effectively use hypermedia-based systems like the web, and the design of systems that are easy to navigate and that provide advanced functionality for transactional activity.     

Measuring task-specific perceptions of the world wide web

This paper describes the development of multi-item scales for measuring user perceptions of the ease-of-use and usefulness of the Web (hereafter web), incorporating a system task focus into the scales dimensional structure (e.g. how easy or useful the web is for information search, communication and or purchasing). The items are tested on 2077 web users recruited using a web survey, revealing four factors for each scale. Perceived ease-of-web use consists of learning, search and find, transaction and communication ease, and perceived web usefulness consists of communication, purchase, information search and acquisition, and access to quality products and information. A regression analysis on web usage frequency shows how easy users find it to learn how to use the web and how useful the web is for purchasing are the best predictors of how frequently they will use the web. These results highlight the importance of training users how to effectively use hypermedia-based systems like the web, and the design of systems that are easy to navigate and that provide advanced functionality for transactional activity.     

一种基于语义匹配的Web信息提取方法研究

为了较好地解决信息过量难以消化、汉语词的歧义划分、Web信息形式不一致并且难以辨识的问题,文章提出了一种基于语义匹配的Web信息提取方法。该方法融合了网页分类、汉语分词、语义信息匹配方法,并给出了一种义素相似度,进而提出了一种基于语义的信息匹配方法来识别和提取网页信息项。基于这种Web信息提取方法的网上药品信息监管系统Web-MIND能够提取出网上药品广告的信息项,并具有较高的准确率。     

基于多阶段匹配的语义Web服务发现框架

随着Web服务的高速发展和广泛应用,如何在众多的Web服务中找出用户所需要的Web服务成为了一个关键的问题.在语义Web服务研究的基础上,提出了一种新的多阶段匹配的语义Web服务发现框架,将整个发现过程分为服务类别、服务功能、服务名称和服务文本语句匹配4个阶段,并在服务功能匹配阶段针对本体库中概念间的密度问题,提出了基于信息量的改进GCSM算法,在服务名称和服务文本语句匹配阶段,针对中文多义词的问题提出了基于实例搭配和基本义原的消歧策略.最后,实验证明提出的发现框架具有较好的可行性和有效性.     

面向在线空间信息的自动化搜索

近年来,越来越多的空间信息实现了在线发布和在线更新。但这些在线空间信息的分布广泛性和发展无序性导致了最终用户难以找到所需的在线空间信息,因此面向在线空间信息的自动化搜索已经成为空间信息共享的一个重要研究内容,其设计目标为自动地帮助用户寻找感兴趣的空间信息。论文从互联网上空间信息的存在形式和提供方式入手,分析了网络空间信息系统的一般结构;通过从搜索对象、搜索方法和用户界面等方面对通用Web信息搜索和面向空间信息搜索进行了比较,得出了实现在线空间信息的自动化搜索必须首先规范化网络空间信息系统的结论,最后总结了面向空间信息的搜索需要解决的困难并分析指出其研究的主要内容。     

Web Usage Mining as a Tool for Personalization: A Survey

This paper is a survey of recent work in the field of web usage mining for the benefitof research on the personalization of Web-based information services. The essence of personalization is the adaptability of information systems to the needs of their users. This issue is becoming increasingly important on the Web, as non-expert users are overwhelmed by the quantity of information available online, while commercial Web sites strive to add value to their services in order to create loyal relationships with their visitors-customers. This article views Web personalization through the prism of personalization policies adopted by Web sites and implementing a variety of functions. In this context, the area of Web usage mining is a valuable source of ideas and methods for the implementation of personalization functionality. We therefore present a survey of the most recent work in the field of Web usage mining, focusing on the problemsthat have been identified and the solutions that have been proposed.     

WEB INFORMATION MONITORING FOR COMPETITIVE INTELLIGENCE

The WWW has become one of the most important media for sharing information. Web information provides another emerging and important avenue and source of competitive intelligence (CI) for companies. CI is critical for companies to stay competitive in the marketplace. Apart from business users, there are other types of CI users such as technical users, casual users, news awareness users and others who would like to be kept informed on the latest development of their interested areas over the WWW. To discover web information, CI users need to constantly monitor certain web sites and web pages for related information. However, the dynamic nature of the web has made such monitoring task complicated and time-consuming. This paper proposes a web monitoring system, WebMon, to help users monitor specified web pages for latest changes and updates in information. Four monitoring functions including date monitoring, keywords monitoring, link monitoring and portion monitoring are supported by the system. The performance of these monitoring functions is also evaluated.     

Virtual Objects in Electronic Catalogs: A Human–Computer Interface Issue

Web interface design is an important aspect of electronic commerce (EC). However, apart from design frameworks and guidelines for web-based EC, not much has been done by researchers or practitioners on how electronic catalogs (e-catalogs) influence the users' desirability and satisfaction as purchasers. In this correspondence, we investigate the form of media that represented the most efficient mode to present products to web users by summarizing and evaluating various existing forms of e-catalogs and their respective responses from web users. We conclude that a 3-D virtual object (VO) is the most efficient mode of electronic cataloging for Web interface due to a better sense of presence of users, a more attractive and enjoyable media of delivery of useful information to users, and a higher level of engagement of user's memory. A 3-D VO, as a result, generates the highest users' satisfaction, which leads to increased propensity to purchase. Further, we discuss the practical and theoretical research implications of these findings to e-catalogs.     

Disambiguating identity web references using Web 2.0 data and semantics

As web users disseminate more of their personal information on the web, the possibility of these users becoming victims of lateral surveillance and identity theft increases. Therefore web resources containing this personal information, which we refer to as identity web references must be found and disambiguated to produce a unary set of web resources which refer to a given person. Such is the scale of the web that forcing web users to monitor their identity web references is not feasible, therefore automated approaches are required. However, automated approaches require background knowledge about the person whose identity web references are to be disambiguated. Within this paper we present a detailed approach to monitor the web presence of a given individual by obtaining background knowledge from Web 2.0 platforms to support automated disambiguation processes. We present a methodology for generating this background knowledge by exporting data from multiple Web 2.0 platforms as RDF data models and combining these models together for use as seed data. We present two disambiguation techniques; the first using a semi-supervised machine learning technique known as Self-training and the second using a graph-based technique known as Random Walks, we explain how the semantics of data supports the intrinsic functionalities of these techniques. We compare the performance of our presented disambiguation techniques against several baseline measures including human processing of the same data. We achieve an average precision level of 0.935 for Self-training and an average f-measure level of 0.705 for Random Walks in both cases outperforming several baselines measures.     

基于互连网的术语定义获取系统

文中介绍了一个实验性的基于互联网的术语定义获取系统,可以方便、迅速的从互连网上查找术语的定义以及与定义有关的内容,给用户迅速获得新生术语以及新技术词汇的定义方面的知识提供方便。系统采用一组术语定义的语言学模式,以多线程方式高效下载网页,并从中匹配符合术语定义模式的文本段落,再经一定后续处理,形成返回给用户的结果。系统中使用的语言学模式是在一定量的科技期刊语料库中获取的。试验结果表明系统的运行效率高,结果的准确度比较令人满意。     

一个基于XML的WEB数据收集模型的研究

目前研究的热门领域Web数据挖掘是从WWW资源上抽取信息(或知识)的过程,是对Web资源中蕴含的、未知的、有潜在应用价值模式的提取。其一般的过程可表示为:信息的发现、信息的选择和预处理、分析过程、产生结果犤1犦。WEB上的数据收集是对WEB数据挖掘的一种支持技术,是WEB数据挖掘的第一步。该文提出了一种基于XML技术的WEB数据收集模型,并实现了其中的一些主要功能。同时针对模型系统的不足做了一些有意义的改进探索。     

面向用户互联网访问日志的异常点击分析

随着互联网用户人数的日益增长,用户行为分析已经成为互联网技术领域重要的研究方法之一。在日志中去除异常点击,对于准确挖掘用户行为的意图和习惯十分重要。该文采用某公司提供的真实用户互联网访问日志,对日志中的连续点击,单IP多用户以及单用户多IP等可能的异常点击,从访问集中度,用户平均访问量等方面进行了分析。我们认为对于连续点击,用户行为分析研究人员可以分情况滤去多余点击或该用户所有点击,而对于单IP多用户和单用户多 IP的点击,我们建议不做处理。     

基于超链接信息的搜索引擎检索结果聚类方法研究

针对目前搜索引擎返回候选信息过多从而使用户不能准确查找与主题有关结果的问题,提出了基于超链接信息的搜索引擎检索结果聚类方法,通过对网页的超链接锚文档和网页文档内容挖掘,最终将网页聚成不同的子类别。这种方法在依据网页内容进行聚类的同时,充分利用了Web结构和超链接信息,比传统的结构挖掘方法更能体现网站文档的内容特点,从而提高了聚类的准确性。     

基于粗糙集的Web事务聚类算法

针对现有Web数据挖掘方法发现的知识和规则存在不精确或不完全的问题,将粗糙集引入到Web挖掘中,进行Web事务聚类.粗糙近似算法基于用户访问序列的顺序和内容建立用户事务相似度矩阵,运用基于相似度矩阵的粗糙上近似提取初始类,使用相对相似性的条件作为合并准则,基于约束相似性的上近似形成后续类.粗糙近似算法能够有效挖掘Web访问日志,聚类Web事务,发现用户访问Web页面的模式.     

Web挖掘在blog空间里的运用

Web挖掘是目前计算机技术领域中的研究热点,它是现代科学技术相互渗透与融合的必然结果。Blog作为一种全新的网络发布模式,在很大程度上增强了网络信息的开放性,吸引着越来越多的网络用户。首先介绍了web数据挖掘的概念,讨论了web数据挖掘的种类,随后对Blog,RSS的特征进行了阐述,最后重点论述了RSS空间里的的数据挖掘。     

Web数据挖掘技术

随着Intemet／Web技术的快速普及和迅猛发展,各种信息可以以非常低的成本在网络上获得。如何在这些信息中找到用户真正需要的内容,成为数据组织和Web相关领域专家学者关注的焦点。Web数据挖掘旨在发现隐藏在Web数据中潜在的有用知识、提供决策支持,已经成为数据挖掘领域中新兴的研究热点。该文主要从Web内容挖掘、Web结构挖掘和Web使用挖掘三个方面阐述Web数据挖掘的基本知识。