An Overlay Architecture for Personalized Object Access and Sharing in a Peer-to-Peer Environment

Due to its exponential growth and decentralized nature, the Internet has evolved into a chaotic repository, making it difficult for users to discover and access resources of interest to them. As a result, users have to deal with the problem of information overload. The Semantic Web's emergence provides Internet users with the ability to associate explicit, self-described semantics with resources. This ability will facilitate in turn the development of ontology-based resource discovery tools to help users retrieve information in an efficient manner. However, it is widely believed that the Semantic Web of the future will be a complex web of smaller ontologies, mostly created by various groups of web users who share a similar interest, referred to as a Community of Interest. This thesis proposes a solution to the information overload problem using a user driven framework, referred to as a Personalized Web, that allows individual users to organize themselves into Communities of Interests based on ontologies agreed upon by all community members. Within this framework, users can define and augment their personalized views of the Internet by associating specific properties and attributes to resources and defining constraint-functions and rules that govern the interpretation of the semantics associated with the resources. Such views can then be used to capture the user's interests and integrate these views into a user-defined Personalized Web. As a proof of concept, a Personalized Web architecture that employs ontology-based semantics and a structured Peer-to-Peer overlay network to provide a foundation of semantically-based resource indexing and advertising is developed. In order to investigate mechanisms that support the resource advertising and retrieval of the Personalized Web architecture, three agent-driven advertising and retrieval schemes, the Aggressive scheme, the Crawler-based scheme, and the Minimum-Cover-Rule scheme, were implemented and evaluated in both stable and churn environments. In addition to the development of a Personalized Web architecture that deals with typical web resources, this thesis used a case study to explore the potential of the Personalized Web architecture to support future web service workflow applications. The results of this investigation demonstrated that the architecture can support the automation of service discovery, negotiation, and invocation, allowing service consumers to actualize a personalized web service workflow. Further investigation will be required to improve the performance of the automation and allow it to be performed in a secure and robust manner. In order to support the next generation Internet, further exploration will be needed for the development of a Personalized Web that includes ubiquitous and pervasive resources

Towards the standard-oriented E-learning : an RDF-based E-learning content management P2P infrastructure and some enabling technologies

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Engineering truly automated data integration and translation systems

This thesis presents an automated, data-driven integration process for relational databases. Whereas previous integration methods assumed a large amount of user involvement as well as the availability of database meta-data, we make no use of meta-data and little end user input. This is done using a novel join and translation finding algorithm that searches for the proper key / foreign key relationships while inferring the instance transformations from one database to another. Because we rely only on the relations that bind the attributes together, we make no use of the database schema information. A novel searching method allows us to search the database for relevant objects without requiring server side indexes or cooperative databases

Ontology-based knowledge management for technology intensive industries

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Complex Relationships and Knowledge Discovery Support in the InfoQuilt System

Support for semantic content is becoming more common in Web-accessible information systems. We see this support emerging with the use of ontologies and machine-readable, annotated documents. The practice of domain modeling coupled with the extraction of domain-specific, contextually relevant metadata also supports the use of semantics. These advancements enable knowledge discovery approaches that define complex relationships between data that is autonomously collected and managed. The InfoQuilt (One of the incarnations of the InfoQuilt system, as applied to the geographic information as part of the NSF Digital Library II initiative is the ADEPT-UGA system [Ade]. This research was funded in part by National Science Foundation grant IIS-9817432.) system supports one such knowledge discovery approach. This paper presents (parts of) the InfoQuilt system with the focus on its use for modeling and utilizing complex semantic inter-domain relationships to enable human-assisted knowledge discovery over Web-accessible heterogeneous data. This includes the specification and execution of Information Scale (IScapes), a semantically rich information request and correlation mechanism