Abstract
Scientific researchers, laboratories and organisations can be profiled and compared by analysing their published works, including documents ranging from academic papers to web sites, blog posts and Twitter feeds. This paper describes how the vector space model from information retrieval, more normally associated with full text search, has been employed in the open source SubSift software to support workflows to profile and compare such collections of documents. SubSift was originally designed to match submitted conference or journal papers to potential peer reviewers based on the similarity between the paper's abstract and the reviewer's publications as found in online bibliographic databases. The software is implemented as a family of RESTful web services that, composed into a re-usable workflow, have already been used to support several major data mining conferences. Alternative workflows and service compositions are now enabling other interesting applications.
Translated title of the contribution | SubSift web services and workflows for profiling and comparing scientists and their published works |
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Original language | English |
Title of host publication | Sixth IEEE International Conference on e-Science (e-Science 2010), Brisbane, Australia |
Publisher | IEEE Computer Society |
Pages | 182 - 189 |
ISBN (Print) | 9780769542904 |
Publication status | Published - Dec 2010 |
Event | IEEE e–Science Conference 2010 - Brisbane, Australia Duration: 7 Dec 2010 → 10 Dec 2010 |
Conference
Conference | IEEE e–Science Conference 2010 |
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Country/Territory | Australia |
City | Brisbane |
Period | 7/12/10 → 10/12/10 |
Bibliographical note
Other: DOI 10.1109/eScience.2010.29Structured keywords
- Jean Golding