2 research outputs found

    User profiling for content personalisation in information retrieval

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    One of the key issues with the overabundance of online information sources is that of finding what is relevant. The key to success for any type of information provider must be the personalisation of content in information retrieval, and this can be achieved through the maintenance of user profiles and the matching of these profiles to content metadata. This paper is concerned with user profiling and its role in content personalisation of information retrieval, and in particular presents a profile model which incorporates user preference information and action history information (representing the user’s previous searches). The benefits and costs of such a model are examined and it is argued that the benefits (including personalisation accuracy, computational costs extensibility and flexibility) far outweigh the costs. The matching of profiles to metadata is also discussed as it fulfils an important role in the personalisation process. Although, the user profile model presented is focused on E-Learning, the general platform could be applied to other areas

    Personalised resource discovery searching over multiple repository types, using user and information provider profiling

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    The success of the Information Society, with the overabundance of online multimedia information, has become an obstacle for users to discover pertinent resources. For those users, the key is the refinement of resource discovery as the choice and complexity of available online content continues to grow. The work resented in this paper will address this issue by representing complex extensible user and information provider profiles and content metadata using XML and the provision of a middle canonical language to aid in learner-to-content matching, independent of the underlying metadata format. This approach can provide a federated search solution leading to personalise resource discovery based on user requirements and preferences, seamlessly searching over multiple repository types. The novelty of the work includes the complex extensible user profiles, information provider profiles, the canonical language and the federated search strategy. Although, the work presented is focused on E-Learning, the general ideas could be applied to any resource discovery or information retrieva
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