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SKIMMR: Machine-Aided Skim-Reading


Vit Novacek, Gully Burns

Publication Type: 
Refereed Conference Meeting Proceeding
Unlike full reading, ’skim-reading’ involves the process of looking quickly over information in an attempt to cover more material whilst still being able to retain a superficial view of the underlying content. Within this work, we specifically emulate this natural human activity by providing a dynamic graph-based view of entities automatically extracted from text using superficial text parsing / processing techniques. We provide a preliminary web-based tool (called ‘SKIMMR’) that generates a network of inter-related concepts from a set of documents. In SKIMMR, a user may browse the network to investigate the lexically-driven information space extracted from the documents. When a particular area of that space looks interesting to a user, the tool can then display the documents that are most relevant to the displayed concepts. We present this as a simple, viable methodology for browsing a document collection (such as a collection scientific research articles) in an attempt to limit the information overload of examining that document collection. This paper presents a motivation and overview of the approach, outlines technical details of the preliminary SKIMMR implementation, describes the tool from the user’s perspective and summarises the related work.
Conference Name: 
Intelligent User Interfaces
ACM Press
Digital Object Identifer (DOI):
Publication Date: 
Conference Location: 
United States of America
Research Group: 
National University of Ireland, Galway (NUIG)
Open access repository: