Stuart N. K. Watt

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Latent Semantic Indexing (LSI) has been shown to be effective in recovering from synonymy and pol-ysemy 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(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)
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)
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)
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)
Blogs are highly rich in opinion making their automatic processing appealing to marketing companies , the media, costumer centres, etc. TREC ran a Blog track in 2006 with two tasks: opinion retrieval and an open task. This document reports the experiments conducted at The Robert Gordon University (RGU) where we used Statistical Language Models combined with(More)