Ibanez A, Larranaga P, Bielza C. "Predicting citation count of Bioinformatics papers within four years of publication " Bioinformatics 25(24):3303-3309, December 15,2009

[Eugene Garfield]

E-mail Addresses: aibanez at fi.upm.es  

TITLE : Predicting citation count of Bioinformatics papers within four 
years of publication 
    
Author(s): Ibanez, A (Ibanez, Alfonso), Larranaga, P (Larranaga, Pedro), 
Bielza, C (Bielza, Concha)  

Source: BIOINFORMATICS    Volume: 25    Issue: 24    Pages: 3303-3309    
Published: DEC 15 2009    
 
Abstract: Motivation: Nowadays, publishers of scientific journals face the 
tough task of selecting high-quality articles that will attract as many 
readers as possible from a pool of articles. This is due to the growth of 
scientific output and literature. The possibility of a journal having a 
tool capable of predicting the citation count of an article within the 
first few years after publication would pave the way for new assessment 
systems.
Results: This article presents a new approach based on building several 
prediction models for the Bioinformatics journal. These models predict the 
citation count of an article within 4 years after publication (global 
models). To build these models, tokens found in the abstracts of 
Bioinformatics papers have been used as predictive features, along with 
other features like the journal sections and 2-week post-publication 
periods. To improve the accuracy of the global models, specific models have 
been built for each Bioinformatics journal section (Data and Text Mining, 
Databases and Ontologies, Gene Expression, Genetics and Population 
Analysis, Genome Analysis, Phylogenetics, Sequence Analysis, Structural 
Bioinformatics and Systems Biology). In these new models, the average 
success rate for predictions using the naive Bayes and logistic regression 
supervised classification methods was 89.4% and 91.5%, respectively, within 
the nine sections and for 4-year time horizon.
 
Document Type: Article  
Language: English  


Reprint Address: Ibanez, A (reprint author), Univ Politecn Madrid, Dept 
Inteligencia Artificial, E-28660 Madrid, Spain  

Addresses: 
1. Univ Politecn Madrid, Dept Inteligencia Artificial, E-28660 Madrid, 
Spain  

E-mail Addresses: aibanez at fi.upm.es  

Publisher: OXFORD UNIV PRESS, GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, 
http://www3.oup.co.uk/jrnls/online  
Discipline: MULTIDISCIPLINARY Current Web Contents  
CC Editions/Collections: Life Sciences (LS)  
IDS Number: 528RJ  
ISSN: 1367-4803