Relying solely on Web browsers to navigate large Web sites has created some navigation problems for users. Many researchers have stressed the importance of improving site user orientation and have suggested the use of information visualisation techniques, in particular "site maps" or "overview diagrams" to address this issue. Link prediction and the semantic relatedness of Web pages have been incorporated into such site maps. This thesis addresses disorientation within Web sites by presenting a visualisation of the site in order to answer one of the three fundamental questions identified by Nielsen and others that users might ask when they become disoriented while navigating a Web site, namely, Where am I now? Where have I been? Where can I go next? A method for making link predictions, which is based on Markov chains, has been developed and implemented in order to answer the third question, "where can I go next?". The method utilises information about the path already followed by the user. In addition to link prediction, pages which are semantically similar to the "current" page are automatically identified using an approach which is based on lexical chains. The proposed approach for link prediction using an exponentially-smoothed transition probability matrix incorporating site usage data over a time period was evaluated by comparing with similar approach developed by Sarukkai. The proposed semantic relatedness approach using weighted lexical chains was empirically compared with an earlier approach developed by Green using synset weight vectors. In conclusion, this thesis argues that Web site link prediction and the identification of semantically-related Web pages can be used to overcome disorientation. The approaches proposed are demonstrated to be superior to earlier methods.

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With the rapid growth of semantic information in the Web, the processes of searching and querying These very large amounts of heterogeneous content have become increasingly challenging. This research tackles the problem of supporting users in querying and exploring information across multiple and heterogeneous Semantic Web (SW) sources. A review of literature on ontology-based Question Answering reveals the limitations of existing technology. Our approach is based on providing a natural language Question Answering interface for the SW, PowerAqua. The realization of PowerAqua represents a considerable advance with respect to other systems, which restrict their scope to an ontology-specific or homogeneous fraction of the publicly available SW content. To our knowledge, PowerAqua is the only system that is able to take advantage of the semantic data available on the Web to interpret and answer user queries posed in natural language. In particular, PowerAqua is uniquely able to answer queries by combining and aggregating information, which can be distributed across heterogeneous semantic resources. Here, we provide a complete overview of our work on PowerAqua, including: the research challenges it addresses; its architecture; the techniques we have realised to map queries to semantic data, to integrate partial answers drawn from different semantic resources and to rank alternative answers; and the evaluation studies we have performed, to assess the performance of PowerAqua. We believe our experiences can be extrapolated to a variety of end-user applications that wish to open up to large scale and heterogeneous structured datasets, to be able to exploit effectively what possibly is the greatest wealth of data in the history of Artificial Intelligence.

The Internet provides interpersonal communication that does not merely emulate the 'real' world but offers radically innovative design options; this study investigates related theoretical contexts to expound new conclusions which recognise both non-pre-existing needs and long-term concerns from an industrial design perspective. The study consists of a contextual section and a practice-related section, and generates preliminary design recommendations in the contextual section as a result of exploring and reviewing: 1) socio-psychological; 2) socio-technological; and 3) technological contexts related to internet interpersonal communication. The preliminary design recommendations are based on the most significant internet interpersonal communication potential identified in the contextual section: 1) the absence of the physical body, 2) the need for artificial interfaces, 3) requirements of human-to-human interaction, and 4) support of controllability. The practice-related section, utilising simulated practice activity, assesses each preliminary design recommendation in terms of its degree of practicality and efficiency, and concludes with an identification of the most important principles for internet interpersonal communication interface and product design as below: a) To design the interface as an efficient self-presenter considering human-tohuman interaction preferentially, and b) To harmonise the technological provisions and distinct internet interpersonal communication opportunities as a benefit for individual users. The preliminary design recommendations are further revised with respect to their hierarchical relations in connection with the principles above, and it is suggested that 'omni-dimensional interface/design' would be a sensible direction for internet interpersonal communication interface and product design as well as for most design disciplines related to information communications technologies. In addition, industrial designers focusing on service design could offer effective and efficient guidance to an industry in which technology is becoming less tangible and in which multidisciplinary collaboration is necessary

Information Extraction (IE) is becoming increasingly important for the semantic analysis of free-text documents stored in large document repositories, such as the Web. Once free-text is analysed for the recognition of concepts and concept interrelations in events and facts of interest, the resulting structured information becomes a valuable knowledge resource. This resource can be of further use in other information management technologies, such as document summarisation, ontology development, semantic document indexing, question answering, etc., or can be further exploited by data mining and reasoning technologies.

In this thesis, a probabilistic approach to the problem of packet forwarding in information centric networks is analysed and further developed. This type of networks are based on information identifiers rather than on the traditional host addresses. The approach is compact forwarding where the Bloom filter is the key method for aggregating forwarding information that allows moving packets at line speed labelled with fiat identifiers. The Bloom filter reduces state at the nodes, simplifies multicast delivery and introduces new trade-offs in the traditional routing and forwarding design space. However) it is a lassy method which produces some potential bandwidth penalties, loops, packet storms, and security issues due to false positives. This thesis focuses on false posit ive control for the probabilistic in-packet forwarding method and proposes two approaches either to reduce false positives or to exploit them in a useful way. One approach consists of a mechanism to carefully select the number of hash functions to use to generate the Bloom filter, The mechanism on average offers the minimum false positive occurrences depending on the traffic along the links. The other approach is a variation of the Bloom filter, the optihash, that can give better performance with respect to the Bloom filter at a cost of slightly more processing. The optihash is constructed with a family of functions that allows an optimisation which can be performed according to different metrics. Two general metrics are proposed in detail and some other, appJicationspeCific, are explored for in-packet forwarding techniques in different types of networks. The time complexity/false positive trade-off is thoroughly investigated and the evaluation of the optihasb as an alternative to the Bloom filter is performed for in-packet compact forwarding.

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