Search (6 results, page 1 of 1)

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Abstract

Purpose - The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach - Over 11.000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings - The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value - No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.

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Abstract

High-precision search results are essential for supporting e-government employees' information tasks. Prior studies have shown that existing features of e-government retrieval systems need improvement in terms of search facilities (e.g., Goh et al. 2008), navigation (e.g., de Jong and Lentz 2006) and metadata (e.g., Kopackova, Michalek and Cejna 2010). This paper investigates how automated categorization can enhance information organization and retrieval, and presents the results of a realistic evaluation that compared automated categorization with free text indexing of the government intranet used by Danish tax authorities. The evaluation demonstrates a potential for automated categorization in a government context. In terms of quantitative measures free text indexing performed at the same level or better than searching by categorization. However, the qualitative analysis revealed that categorized overviews were useful if the participant did not possess much knowledge of the task at hand. When task knowledge was present, categorization was used to support the assumptions of a correct search. Participants avoided automated categorization if high-precision documents were among the top results or if few documents were retrieved. The findings emphasise the importance of simultaneous search options for e-government IR systems, and reveal that automated categorization is valuable in improving search facilities in e-government.

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Abstract

Tools for automatic subject assignment help deal with scale and sustainability in creating and enriching metadata, establishing more connections across and between resources and enhancing consistency. Although some software vendors and experimental researchers claim the tools can replace manual subject indexing, hard scientific evidence of their performance in operating information environments is scarce. A major reason for this is that research is usually conducted in laboratory conditions, excluding the complexities of real-life systems and situations. The article reviews and discusses issues with existing evaluation approaches such as problems of aboutness and relevance assessments, implying the need to use more than a single "gold standard" method when evaluating indexing and retrieval, and proposes a comprehensive evaluation framework. The framework is informed by a systematic review of the literature on evaluation approaches: evaluating indexing quality directly through assessment by an evaluator or through comparison with a gold standard, evaluating the quality of computer-assisted indexing directly in the context of an indexing workflow, and evaluating indexing quality indirectly through analyzing retrieval performance.

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Abstract

Transferring scientific knowledge between universities and industry is known to be problematic, specifically for small and medium-sized enterprises (SMEs) that have limited resources and absorption capacity. A variety of channels is used for knowledge transfer. These include what is commonly referred to as generic pathways (e.g., scientific publications) and relational pathways (e.g., faculty consulting). The purpose of this research is to extend our knowledge about the design of knowledge organization for a generic pathway interface providing access to scientific knowledge in a research information management system. The analysis focuses on how to meet the characteristics of SMEs in the design and organisation of the subject terms and annotations in the navigation and searching system. The design is based on findings from a qualitative analysis of eight SMEs and on principles of experience design. Experience design was applied, because the classical KO design qualities seem not to be comprehensive goals for knowledge organisation for a generic pathway interface. The SMEs need guidance, encouragement, and inspiration. Experience designs are designs that have been created to provoke changes in a user's state and behaviour by engaging this user emotionally and cognitively. The paper provides examples and discusses the outcome of the experience dimensions.

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Abstract

Professional, workplace searching is different from general searching, because it is typically limited to specific facets and targeted to a single answer. We have developed the semantic component (SC) model, which is a search feature that allows searchers to structure and specify the search to context-specific aspects of the main topic of the documents. We have tested the model in an interactive searching study with family doctors with the purpose to explore doctors' querying behaviour, how they applied the means for specifying a search, and how these features contributed to the search outcome. In general, the doctors were capable of exploiting system features and search tactics during the searching. Most searchers produced well-structured queries that contained appropriate search facets. When searches failed it was not due to query structure or query length. Failures were mostly caused by the well-known vocabulary problem. The problem was exacerbated by using certain filters as Boolean filters. The best working queries were structured into 2-3 main facets out of 3-5 possible search facets, and expressed with terms reflecting the focal view of the search task. The findings at the same time support and extend previous results about query structure and exhaustivity showing the importance of selecting central search facets and express them from the perspective of search task. The SC model was applied in the highest performing queries except one. The findings suggest that the model might be a helpful feature to structure queries into central, appropriate facets, and in returning highly relevant documents.

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Abstract

CHAOS (Cultural Heritage Archive Open System) provides streaming access to more than 500,000 broadcasts by the Danish Broadcast Corporation from 1931 and onwards. The archive is part of the LARM project with the purpose of enabling researchers to search, annotate, and interact with recordings. To support the researchers the optimal way, a user-centred approach was taken to develop the platform and related metadata scheme. Based on the requirements, a three level metadata scheme was developed: 1) core archival metadata, 2) LARM metadata, and 3) project-specific metadata. The paper analyses how researchers apply the metadata scheme in their research work. The purpose is to gain insight into broadcast researchers' tagging practice and motivation for tagging to inform future design of digital cultural heritage systems. The study consists of two studies, a) a qualitative study of subjects and vocabulary of the applied metadata and annotations, and b) five semi-structured interviews about goals for tagging. The findings clearly show that the primary role of LARM.fm is to provide access to broadcasts and provide tools to segment and manage concrete segments of radio broadcasts. Although the assigned metadata are project-specific, they have been applied to serve as invaluable access points for fellow researchers due to their factual and neutral nature. The researchers particularly stress LARM.fm's strength in providing streaming access to a large, shared corpus of broadcasts.