7 research outputs found
Augmenting the Evaluation and Mapping of Progress in Scientific Research:A Human-Machine Symbiosis Perspective
Collaborative Literature Search System:An Intelligence Amplification Method for Systematic Literature Search
2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC) Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC)
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Augmenting the Evaluation and Mapping of Progress in Scientific Research: A Human-Machine Symbiosis Perspective
In this paper we propose and demonstrate a software tool for symbiotic human-machine analysis, applicable for structured literature reviews (SLR). We present a seed-based search of bibliographic information, resulting in document clustering and graph visualization. Through a collaborative human-machine effort we show how to detect potential bridging articles and paradigm shifts. The overarching goal is to support the SLR process, especially for developing fields of science, as well as interdisciplinary fields, where similar concepts can be overlooked as they are associated with different keywords and belong to different groups, yet share common ideas. Finally, we demonstrate the application of the tool with two literature search and visualization examples
Collaborative Literature Search System: An Intelligence Amplification Method for Systematic Literature Search
In this paper, we present a method for systematic literature search based on the symbiotic partnership between the human researcher and intelligent agents. Using intelligence amplification, we leverage the calculation power of computers to quickly and thoroughly extract data, calculate measures, and visualize relationships between scientific documents with the ability of domain experts to perform qualitative analysis and creative reasoning. Thus, we create a foundation for a collaborative literature search system (CLSS) intended to aid researches in performing literature reviews, especially for interdisciplinary and evolving fields of science for which keyword-based literature searches result in large collections of documents beyond humans’ ability to process or the extensive use of filters to narrow the search output risks omitting relevant works. Within this article, we propose a method for CLSS and demonstrate its use on a concrete example of a literature search for a review of the literature on human-machine symbiosis