cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications

Persistent Link:
http://hdl.handle.net/10150/105672
Title:
cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications
Author:
Dervos, Dimitris A.; Kalkanis, Thomas
Citation:
cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications 2005, Workshop Proceedings:668-673
Publisher:
IEEE
Issue Date:
2005
Description:
The present item comprises an amended (post-print) version of: D.A. Dervos and T. Kalkanis, cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications, Third IEEE International Workshop on Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Proceedings pp. 668-673, Sofia, Bulgaria, September 5-7, 2005
URI:
http://hdl.handle.net/10150/105672
Submitted date:
2006-04-09
Abstract:
A new framework is proposed for the calculation of impact factor ratings of research publications. Given a collection of research articles, the corresponding citations graph is constructed in the form of a relational table. The impact value is considered at the article level, and is calculated by considering not only the citations made directly to an article, but also citations made to the corresponding citing article(s). In this respect, an improved algorithm is utilized, namely one that traverses all the threads in the citations graph, in an attempt to improve the degree of fairness in assigning credit for the impact value of each one article. When two articles have an equal number of (direct) citations, the one that has triggered more research activity (i.e. its citing articles attract a larger number of citations at subsequent levels in the citations graph) is assigned a higher impact value and, consequently, is ranked to be better.
Type:
Conference Paper
Language:
en
Keywords:
Bibliometrics; Citation Analysis
Local subject classification:
citation graph; impact factor; citation analysis

Full metadata record

DC FieldValue Language
dc.contributor.authorDervos, Dimitris A.en_US
dc.contributor.authorKalkanis, Thomasen_US
dc.date.accessioned2006-04-09T00:00:01Z-
dc.date.available2010-06-18T23:31:40Z-
dc.date.issued2005en_US
dc.date.submitted2006-04-09en_US
dc.identifier.citationcc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications 2005, Workshop Proceedings:668-673en_US
dc.identifier.urihttp://hdl.handle.net/10150/105672-
dc.descriptionThe present item comprises an amended (post-print) version of: D.A. Dervos and T. Kalkanis, cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications, Third IEEE International Workshop on Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Proceedings pp. 668-673, Sofia, Bulgaria, September 5-7, 2005en_US
dc.description.abstractA new framework is proposed for the calculation of impact factor ratings of research publications. Given a collection of research articles, the corresponding citations graph is constructed in the form of a relational table. The impact value is considered at the article level, and is calculated by considering not only the citations made directly to an article, but also citations made to the corresponding citing article(s). In this respect, an improved algorithm is utilized, namely one that traverses all the threads in the citations graph, in an attempt to improve the degree of fairness in assigning credit for the impact value of each one article. When two articles have an equal number of (direct) citations, the one that has triggered more research activity (i.e. its citing articles attract a larger number of citations at subsequent levels in the citations graph) is assigned a higher impact value and, consequently, is ranked to be better.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectBibliometricsen_US
dc.subjectCitation Analysisen_US
dc.subject.othercitation graphen_US
dc.subject.otherimpact factoren_US
dc.subject.othercitation analysisen_US
dc.titlecc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publicationsen_US
dc.typeConference Paperen_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.