Paper Info
Title
Serving the readers of scholarly documents: A grand challenge for the introspective digital library
Abstract
The scholarly literature produced by human civilization will soon be considered small data, able to be portably conveyed by the network and carried on personal machines. This semi-structured text centric knowledge base is a focus of attention for scholars, as the wealth of facts, facets and connections in scholarly documents are large. Such machine analysis can derive insights that can inform policy makers, academic and industrial management, as well as scholars as authors themselves. There is another underserved community of scholarly document users that has been overlooked: the readers themselves. I call for the community to put more efforts towards supporting our own scholars (especially beginning scholars, new to the research process) with automation from information retrieval and natural language processing. Techniques that mine information from within the full text of a document could be used to introspect a digital library's materials, inferring better search metadata, improving scholarly document recommendation, and aiding the understanding of the text, figures, presentations and citations of our scholarly literature. Such an introspective digital library will enable scholars to assemble an understanding of other scholars' work more efficiently, and provide downstream machine reading applications with input for their analytics.
Year
DOI
Venue
2015
10.1109/35021BIGCOMP.2015.7072807
BigComp
Keywords
Field
DocType
search metadata,digital library,digital libraries,information retrieval,scholarly document recommendation,scholarly literature,scholarly document readers,natural language processing,machine reading applications,big data,knowledge based systems
Introspection,Metadata,World Wide Web,Civilization,Computer science,Knowledge-based systems,Knowledge base,Digital library,Analytics,Big data
Conference
ISSN
Citations 
PageRank 
2375-933X
0
0.34
References 
Authors
21
1
Name
Order
Citations
PageRank
Min-yen Kan12786162.35