Web services have emerged as a de facto standard for encapsulating services within or across organization boundaries. Various proposals have been made to compose Web services into workflow so as to meet the goal previously unaccomplished by a single entity. This thesis intends to investigate the Web services-based workflow access control problem. It starts by analyzing the various access control constraints proposed in the literatures and presenting three primitive constructs that are capable of specify these constraints. It then proposes a Web service selection approach that dynamically chooses a performer for each task in the workflow, not only to satisfy all access control constraints currently but also to increase the chance of completing the entire process in the future. The proposed approach is evaluated using synthetic data and is shown to result in the execution that is less likely to violate any specified access control constraints.

Web services have become the de facto standards as components for quickly building a business process that satisfies the business goal of an organization. Nowadays, Web services have found its way into describing the functions of automatic tasks as well as manual tasks. An important part in the specification of a business process, especially for manual tasks, is the access control. This thesis considers both types of tasks involved in a Web services-based process with its corresponding access control problem and proposes a selection approach for choosing the performer for each task so as to satisfy all access control constraints. Based on the role-based access control model, we focus on two types of access control: separation of duties (SoD) and binding of duties (BoD). Both role-level and participant-level of SoDs and of BoDs that need to be dynamically enforced and these constraints are considered in this thesis. The proposed performer selection approach is evaluated by a workflow scenario and is shown to have the highest chance of satisfying all predefined access control constraints when compared to other methods.

Due to the information explosion on the Internet, effective information search techniques are required to retrieve the desired information from the Web. Based on much analysis on users' search intention and the variant forms of Web content, we find that both the query and the indexed web content are often associated with various context information, which can provide much essential information to indicate the ranking relevance in Web search. This dissertation seeks to develop new search algorithms and techniques by taking advantage of rich context information to improve search quality and consists of two major parts. In the first part, we study the context of the query in terms of various ranking objectives of different queries. In order to improve the ranking relevance, we propose to incorporate such query context information into the ranking model. Two general approaches will be introduced in the following of this dissertation. The first one proposes to incorporate query difference into ranking by introducing query-dependent loss functions, by optimizing which we can obtain better ranking model. Then, we investigate another approach which applies a divide-and-conquer framework for ranking specialization. The second part of this dissertation investigates how to extract the context of specific Web content and explore them to build more effective search system. This study is based on the new emerging social media content. Unlike traditional Web content, social media content is inherently associated with much new context information, including content semantics and quality, user reputation, and user interactions, all of which provide useful information for acquiring knowledge from social media. In this dissertation, we seek to develop algorithms and techniques for effective knowledge acquisition from collaborative social media environments by using the dynamic context information. We first propose a new general framework for searching social media content, which integrates both the content features and the user interactions. Then, a semi-supervised framework is proposed to explicitly compute content quality and user reputation, which are incorporated into the search framework to improve the search quality. Furthermore, this dissertation also investigates techniques for extracting the structured semantics of social media content as new context information, which is essential for content retrieval and organization.

Ein zentraler Vorteil des Webs gegenüber herkömmlichen Anwendungsplattformen stellt sein großes Potential dar, Aufgaben über Organisationsgrenzen hinweg zu unterstützen. Derzeit lassen sich Tendenzen zu einer Klasse von föderativen Web-Anwendungen beobachten, die dieses Potential verstärkt ausschöpfen. Eine besondere Herausforderung bei ihrer Entwicklung ergibt sich durch die Ausrichtung der Zugangskontrolle auf zugreifende Benutzer, deren Identitäten von Partnerorganisationen verwaltet werden. Die Arbeit erweitert den Stand der Technik im Bereich Web Engineering um Werkzeuge, Modelle, Methoden und Prozesse zum gezielten Unterstützen der Evolution föderativer Systeme. Sie umfasst einen Katalog aus Entwurfsbausteinen für föderative Infrastrukturen, eine Modellierungssprache zur Planung der föderativen Architektur sowie eine Methode zur Integration föderativ geschützter Informationsräume in Web-Anwendungen. / A central advantage of the Web over traditional application plattforms lies in its great potential for supporting tasks beyond organizational boundaries. Presently, a trend towards a new class of federated Web applications can be observed that exploit this potential to a high degree. The development of such applications is particularly challenged by the need for controlling accesses of users whose identities are managed by partner organizations. This work extends the state of the art in the area of Web Engineering with tools, models, methods and processes for supporting the evolution of federated systems. It comprises a catalogue of design building blocks for federated infrastructures, a modeling language for planning federated architectures as well as a method for integrating information spaces of applications that are subject to federated access control.

Univ., Diplomarbeit u.d.T.: Klossek, Martin: Optimierung der Personalisierung im Internet durch kollaboratives Filtern--Frankfurt (Main), 2003.

Berlin, Freie Universität, Thesis (doctoral), 2000.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 83-91). Also available in electronic version. Access restricted to campus users.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 170-181). Also available in electronic version. Access restricted to campus users.

Artificial Intelligence Lab, Department of MIS, Univeristy of Arizona / It has become increasingly difficult to locate relevant information on the Web, even with the help of Web search engines. Two approaches to addressing the low precision and poor presentation of search results of current search tools are studied: meta-search and document categorization. Meta-search engines improve precision by selecting and integrating search results fromgeneric or domain-specific Web search engines or other resources. Document categorization promises better organization and presentation of retrieved results. This article introduces MetaSpider, a meta-search engine that has real-time indexing and categorizing functions. We report in this paper the major components of MetaSpider and discuss related technical approaches. Initial results of a user evaluation study comparing Meta- Spider, NorthernLight, and MetaCrawler in terms of clustering performance and of time and effort expended show that MetaSpider performed best in precision rate, but disclose no statistically significant differences in recall rate and time requirements. Our experimental study also reveals that MetaSpider exhibited a higher level of automation than the other two systems and facilitated efficient searching by providing the user with an organized, comprehensive view of the retrieved documents.

Purpose: To provide a critical review of Bergmanâ s 2001 study on the Deep Web. In addition, we bring a new concept into the discussion, the Academic Invisible Web (AIW). We define the Academic Invisible Web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the Invisible Web is central to scientific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estimation based on infor-metric laws. Literature review on approaches for uncovering information from the Invisible Web. Findings: Bergmanâ s size estimation of the Invisible Web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimation is given. Research limitations/implications: The precision of our estimation is limited due to small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the Academic Invisible Web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search en-gines with data on the size and attributes of the Academic Invisible Web.