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  • × author_ss:"Pejtersen, A.M."
  1. Pejtersen, A.M.: ¬The role of domain, task and users in providing subject access to information (1993) 0.00
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    Abstract
    Decribes the BookHouse, a system for the retrieval and indexing of fiction and non fiction literature developed for public and school libraries though cooperation between library and information science professionals. Discusses 3 aspects of the system: domain characteristic; task analysis; and user characteristics. Outlines the framework underlying the collection of field data with special emphasis on the work involved in transforming the empirical field studies of user behaviour in the library into computer system specifications and subsequent design of a retrieval system providing subject access to fiction. Describes a few of the many indexing policies, rules and practices which evolved for concept identification and book descriptions as well as the functionality and associated displays of the system for supporting the retrieval and indexing of fiction
  2. Pejtersen, A.M.: Interfaces based on associative semantics for browsing in information retrieval (1990) 0.00
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  3. Albrechtsen, H.; Andersen, H.H.K.; Cleal, B.; Pejtersen, A.M.: Categorical complexity in knowledge integration : empirical evaluation of a cross-cultural film research collaboratory (2004) 0.00
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    Source
    Knowledge organization and the global information society: Proceedings of the 8th International ISKO Conference 13-16 July 2004, London, UK. Ed.: I.C. McIlwaine
  4. Pejtersen, A.M.; Albrechtsen, H.: Models for collaborative integration of knowledge (2003) 0.00
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    Abstract
    Collaborative integration of knowledge in distributed and cross-disciplinary work domains poses a number of challenges to classification, comprising: 1) how to analyze the actors' current practice of integration of knowledge and 2) how to model consistent semantic support of diverse interpretive perspectives among the actors. This paper introduces a cognitive systems engineering approach to modelling collaborative integration of knowledge in work domains. A generic means-ends model provides a theoretical foundation for mapping the territory of collaborative work. A decision task model captures the actors' distributed decision-making in integration of knowledge. The problem of collaborative integration of knowledge in a distributed web-based film collaboratory is explored through an empirical case of collaborative film indexing. The empirical study identified a lack of tools for consistent support of integration of knowledge. The means-ends model and the decision task model guided the design of a conceptual structure of the common workspace of film indexing. The paper concludes with a proposal for further work an models for integration of knowledge through ecological classification schemes. 1. Introduction Current work practice and knowledge production to an increasing degree involves actors from different disciplines, cultures and organisations. Additionally, current work practice not only relies an authoritative orderings of knowledge, but also relies an the dynamism of the actors' ongoing collaborative integration of knowledge, i.e. their shared interpretations of knowledge, exchange of perspectives and joint knowledge production. Consequently, in order to support the actors' ongoing collaborative integration of knowledge, the design of support tools, like classification schemes, must address not only the order of knowledge, but also the situational contexts where collaborative integration of knowledge occurs. This paper introduces an ecological approach to integration of knowledge across boundaries in distributed collaboratory work environments, which is founded an (a) work domain analysis (b) the development of models for collaborative integration of knowledge. The work domain analysis is based an means-ends analysis of the territory of work and the actors' information needs during decision making. The result is conceptual structures of collaborative work that can be used to create collaborative classification schemes. Previous work an design of ecological classification schemes proposed that such schemes should be based an a finegrained empirical analysis of actors' collaborative decision tasks in order to identify the knowledge produced and needed by the actors (Pejtersen & Albrechtsen, 2000).