Stuart N. K. Watt

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Latent Semantic Indexing (LSI) has been shown to be effective in recovering from synonymy and polysemy in text retrieval applications. However, since LSI ignores class labels of training documents, LSI generated representations are not as effective in classification tasks. To address this limitation, a process called ‘sprinkling’ is presented. Sprinkling is(More)
We present a novel approach to mine word similarity in Textual Case Based Reasoning. We exploit indirect associations of words, in addition to direct ones for estimating their similarity. If word A co-occurs with word B, we say A and B share a first order association between them. If A co-occurs with B in some documents, and B with C in some others, then A(More)
Case Retrieval Networks (CRNs) facilitate flexible and efficient retrieval in Case-Based Reasoning (CBR) systems. While CRNs scale up well to handle large numbers of cases in the case-base, the retrieval efficiency is still critically determined by the number of feature values (referred to as Information Entities) and by the nature of similarity relations(More)
Current e-Book browsers provide minimal support for comprehending the organization, narrative structure, and themes, of large complex books. In order to build an understanding of such books, readers should be provided with user interfaces that present, and relate, the organizational, narrative and thematic structures. We propose adapting information(More)
The categorization of documents is traditionally topic-based. This paper presents a complementary analysis of research and experiments on genre to show that encouraging results can be obtained by using genre structure (form) features. We conducted an experiment to assess the effectiveness of using eXtensible Mark-Up Language (XML) tag information, and(More)
This paper reports on an approach to the analysis of form (layout and formatting) during genre recognition recorded using eye tracking. The researchers focused on eight different types of e-mail, such as calls for papers, newsletters and spam, which were chosen to represent different genres. The study involved the collection of oculographic behaviour data(More)
In this paper we present the concept of Federated Information Sharing Communities (FISC), which leverages organisational and social relationships with document content to provide community-centred information sharing and communication environments. Prominence is given to capabilities that go beyond the generic retrieval of documents to include the ability(More)
In this paper we describe the concept of Federated Information Sharing Communities (FISC), and associated architecture, which provide a way for organisations, distributed workgroups and individuals to build up a federated community based on their common interests over the World Wide Web. To support communities, we develop capabilities that go beyond the(More)