Evaluating multi-criteria Connection mechanisms: A new algorithm for browsing digital archives.

Searching for articles of interest in a digital archive need not be through a free-form text search. In fact, many authors have suggested that the best way to find relevant items in an archive is to browse its contents rather than to search for specific keywords. The University of Central Florida’s...

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Publicado en:Digital Scholarship in the Humanities Vol. 33; no. 3; pp. 540 - 548
Autores principales: Giroux, Amy Larner, Harper, Connie, Wiegand, R Paul
Formato: Artículo
Publicado: Oxford University Press / USA Sep2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Giroux, Amy Larner
          Harper, Connie
          Wiegand, R Paul
        affil:
          Center for Humanities and Digital Research, University of Central Florida (UCF), Orlando, FL, USA
          RICHES, Department of History, University of Central Florida (UCF), Orlando, FL, USA
          Institute for Simulation and Training, University of Central Florida (UCF)), Orlando, FL, USA
      su:
        Multiple criteria decision making
        Digital libraries
        Algorithms
        Web browsing
        University of Central Florida
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          Multiple criteria decision making
          Digital libraries
          Algorithms
          Web browsing
          University of Central Florida
      ab: Searching for articles of interest in a digital archive need not be through a free-form text search. In fact, many authors have suggested that the best way to find relevant items in an archive is to browse its contents rather than to search for specific keywords. The University of Central Florida’s Regional Initiative for Collecting Histories, Experiences and Stories (RICHES) project uses a multi-criteria Connections algorithm to make item selection recommendations and browse through the RICHES Mosaic Interface (RICHES MI)—an archive of digitized historical documents, imagery, and audio. The Connections algorithm allows researchers to examine a selected artifact and nearest related items in the archive based on multiple criteria from the metadata contained in the artifact of interest. To determine how effective the Connections algorithm was at presenting relevant material, it was compared to random selections and single criteria keyword searches. In this article we will show that the multi-criteria approach is not only better than randomly selected results it also selects more relevant items than single criteria keyword searches. In addition, the multi-criteria algorithm achieves a secondary benefit: it returns unanticipated relevant results that potentially yield new insights for the researcher.
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    language: English
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