1,962 research outputs found

    Facets and Typed Relations as Tools for Reasoning Processes in Information Retrieval

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    Faceted arrangement of entities and typed relations for representing different associations between the entities are established tools in knowledge representation. In this paper, a proposal is being discussed combining both tools to draw inferences along relational paths. This approach may yield new benefit for information retrieval processes, especially when modeled for heterogeneous environments in the Semantic Web. Faceted arrangement can be used as a se-lection tool for the semantic knowledge modeled within the knowledge repre-sentation. Typed relations between the entities of different facets can be used as restrictions for selecting them across the facets

    Redesigning Information Resources for Digital Natives

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    The influx of Digital Natives into higher education, combined with the introduction of virtual learning environments as the primary means of interaction between students and universities, will have a transformational effect on learning and on library services. This paper examines the e-book market-place and the main UK responses to it (the Southern Universities Purchasing Consortium’s tender and the JISC E-Books Observatory project). Within this context the innovative measures already taken by Bournemouth University are discussed, as are plans to develop innovative pedagogic frameworks and an e-reading strategy through a Higher Education Academy-funded pathfinder project, Innovative E-Learning with E-Resources (eRes)

    Using the Annotated Bibliography as a Resource for Indicative Summarization

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    We report on a language resource consisting of 2000 annotated bibliography entries, which is being analyzed as part of our research on indicative document summarization. We show how annotated bibliographies cover certain aspects of summarization that have not been well-covered by other summary corpora, and motivate why they constitute an important form to study for information retrieval. We detail our methodology for collecting the corpus, and overview our document feature markup that we introduced to facilitate summary analysis. We present the characteristics of the corpus, methods of collection, and show its use in finding the distribution of types of information included in indicative summaries and their relative ordering within the summaries.Comment: 8 pages, 3 figure

    Facilitating design learning through faceted classification of in-service information

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    The maintenance and service records collected and maintained by engineering companies are a useful resource for the ongoing support of products. Such records are typically semi-structured and contain key information such as a description of the issue and the product affected. It is suggested that further value can be realised from the collection of these records for indicating recurrent and systemic issues which may not have been apparent previously. This paper presents a faceted classification approach to organise the information collection that might enhance retrieval and also facilitate learning from in-service experiences. The faceted classification may help to expedite responses to urgent in-service issues as well as to allow for patterns and trends in the records to be analysed, either automatically using suitable data mining algorithms or by manually browsing the classification tree. The paper describes the application of the approach to aerospace in-service records, where the potential for knowledge discovery is demonstrated

    Optimising metadata to make high-value content more accessible to Google users

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    Purpose: This paper shows how information in digital collections that have been catalogued using high-quality metadata can be retrieved more easily by users of search engines such as Google. Methodology/approach: The research and proposals described arose from an investigation into the observed phenomenon that pages from the Glasgow Digital Library (gdl.cdlr.strath.ac.uk) were regularly appearing near the top of Google search results shortly after publication, without any deliberate effort to achieve this. The reasons for this phenomenon are now well understood and are described in the second part of the paper. The first part provides context with a review of the impact of Google and a summary of recent initiatives by commercial publishers to make their content more visible to search engines. Findings/practical implications: The literature research provides firm evidence of a trend amongst publishers to ensure that their online content is indexed by Google, in recognition of its popularity with Internet users. The practical research demonstrates how search engine accessibility can be compatible with use of established collection management principles and high-quality metadata. Originality/value: The concept of data shoogling is introduced, involving some simple techniques for metadata optimisation. Details of its practical application are given, to illustrate how those working in academic, cultural and public-sector organisations could make their digital collections more easily accessible via search engines, without compromising any existing standards and practices

    Subject Classification of Collection-level Descriptions Using DDC for Information Landscaping

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    Collection-level description (CLD) has emerged as an important tool for facilitating user access to large heterogeneous collections within digital library and hybrid information environments. Such metadata enables "information landscaping" techniques to be deployed, thereby allowing users to survey, discover and identify relevant collections. This can aid the precision of item-level queries by eliminating collections which may produce a significant number of false-drops or may contain no relevant items. The ability to provide suitable subject indexing and subject-based organization within such collection-level environments is an increasingly important user requirement, particularly for landscaping; yet it remains highly problematic owing to, for example, the broad subject coverage of many collections and the item-level nature of controlled vocabularies. In this paper we propose a methodology for the subject designation of collections using the Dewey Decimal Classification (DDC). The proposed approach allows the establishment of reliable, consistent and meaningful DDC class numbers to facilitate improved user browsing and searching tools within CLD systems. The methodology will be demonstrated using the Scottish Collections Network (SCONE) and alternative techniques to facilitate general subject analysis will also discussed

    An Ontological Framework for Knowledge Management in Systems Engineering Processes

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    ISBN:978-953-7619-94-7, pp.149-168Systems Engineering (SE) processes comprise highly creative and knowledge-intensive tasksthat involve extensive problem-solving and decision-making activities amonginterdisciplinary teams (Meinadier, 2002). SE projects involve the definition of multipleartifacts that present different formalization degrees, such as requirements specification,system architecture, and hardware/ software components. Transitions between the projectphases stem from decision making processes supported both by generally available domainand design knowledge.We argue that Knowledge about engineering processes constitutes one of the most valuableassets for SE organizations. Most often, this knowledge is only known implicitly, relyingheavily on the personal experience background of system engineers. To fully exploit thisintellectual capital, it must be made explicit and shared among project teams. Consistentand comprehensive knowledge management methods need to be applied to capture andintegrate the individual knowledge items emerging in the course of a system engineeringproject

    Predicting Text Quality: Metrics for Content, Organization and Reader Interest

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    When people read articles---news, fiction or technical---most of the time if not always, they form perceptions about its quality. Some articles are well-written and others are poorly written. This thesis explores if such judgements can be automated so that they can be incorporated into applications such as information retrieval and automatic summarization. Text quality does not involve a single aspect but is a combination of numerous and diverse criteria including spelling, grammar, organization, informative nature, creative and beautiful language use, and page layout. In the education domain, comprehensive lists of such properties are outlined in the rubrics used for assessing writing. But computational methods for text quality have addressed only a handful of these aspects, mainly related to spelling, grammar and organization. In addition, some text quality aspects could be more relevant for one genre versus another. But previous work have placed little focus on specialized metrics based on the genre of texts. This thesis proposes new insights and techniques to address the above issues. We introduce metrics that score varied dimensions of quality such as content, organization and reader interest. For content, we present two measures: specificity and verbosity level. Specificity measures the amount of detail present in a text while verbosity captures which details are essential to include. We measure organization quality by quantifying the regularity of the intentional structure in the article and also using the specificity levels of adjacent sentences in the text. Our reader interest metrics aim to identify engaging and interesting articles. The development of these measures is backed by the use of articles from three different genres: academic writing, science journalism and automatically generated summaries. Proper presentation of content is critical during summarization because summaries have a word limit. Our specificity and verbosity metrics are developed with this genre as the focus. The argumentation structure of academic writing lends support to the idea of using intentional structure to model organization quality. Science journalism articles convey research findings in an engaging manner and are ideally suited for the development and evaluation of measures related to reader interest
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