Show simple item record

dc.contributor.authorBlake, Catherine
dc.contributor.authorAnderson, Caryn
dc.date.accessioned2009-01-14T00:00:01Z
dc.date.available2010-06-18T23:32:56Z
dc.date.issued2005en_US
dc.date.submitted2009-01-14en_US
dc.identifier.citationThe Shift from Information Retrieval to Information Synthesis 2005,en_US
dc.identifier.urihttp://hdl.handle.net/10150/105714
dc.description.abstractGrand challenges such as public health, security, genomics, environmental protection, education, and economics, are characterized by complexity, interdependence, globalization, and unpredictability. Although the unprecedented quantity of information surrounding these challenges can provide users with a new perspective on solutions, the data surrounding complex systems vary with respect to levels of structure and authority, and include vastly different contexts and vocabularies. To be successful in this domain we must extend our models of information science such that they operate successfully in environments where the quantity of relevant information far exceeds our human processing capacity. For example, the well-accepted precision and recall metrics break down when hundreds of thousands of documents are relevant. Solutions to grand challenges require that information scientists shift their focus from information retrieval towards information synthesis.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.subjectKnowledge Managementen_US
dc.subjectInformation Extractionen_US
dc.subjectInformation Retrievalen_US
dc.subjectInterdisciplinarityen_US
dc.subjectInformation Seeking Behaviorsen_US
dc.subjectInformation Analysisen_US
dc.titleThe Shift from Information Retrieval to Information Synthesisen_US
dc.typeConference Paperen_US
refterms.dateFOA2018-06-24T22:11:12Z
html.description.abstractGrand challenges such as public health, security, genomics, environmental protection, education, and economics, are characterized by complexity, interdependence, globalization, and unpredictability. Although the unprecedented quantity of information surrounding these challenges can provide users with a new perspective on solutions, the data surrounding complex systems vary with respect to levels of structure and authority, and include vastly different contexts and vocabularies. To be successful in this domain we must extend our models of information science such that they operate successfully in environments where the quantity of relevant information far exceeds our human processing capacity. For example, the well-accepted precision and recall metrics break down when hundreds of thousands of documents are relevant. Solutions to grand challenges require that information scientists shift their focus from information retrieval towards information synthesis.


Files in this item

Thumbnail
Name:
BlakeAnderson.pdf
Size:
18.07Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record