TY - GEN
T1 - On the use of similarity search to detect fake scientific papers
AU - Williams, Kyle
AU - Giles, C. Lee
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Fake scientific papers have recently become of interest within the academic community as a result of the identification of fake papers in the digital libraries of major academic publishers [8]. Detecting and removing these papers is important for many reasons. We describe an investigation into the use of similarity search for detecting fake scientific papers by comparing several methods for signature construction and similarity scoring and describe a pseudo-relevance feedback technique that can be used to improve the effectiveness of these methods. Experiments on a dataset of 40,000 computer science papers show that precision, recall and MAP scores of 0.96, 0.99 and 0.99, respectively, can be achieved, thereby demonstrating the usefulness of similarity search in detecting fake scientific papers and ranking them highly.
AB - Fake scientific papers have recently become of interest within the academic community as a result of the identification of fake papers in the digital libraries of major academic publishers [8]. Detecting and removing these papers is important for many reasons. We describe an investigation into the use of similarity search for detecting fake scientific papers by comparing several methods for signature construction and similarity scoring and describe a pseudo-relevance feedback technique that can be used to improve the effectiveness of these methods. Experiments on a dataset of 40,000 computer science papers show that precision, recall and MAP scores of 0.96, 0.99 and 0.99, respectively, can be achieved, thereby demonstrating the usefulness of similarity search in detecting fake scientific papers and ranking them highly.
UR - http://www.scopus.com/inward/record.url?scp=84951798118&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84951798118&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-25087-8_32
DO - 10.1007/978-3-319-25087-8_32
M3 - Conference contribution
AN - SCOPUS:84951798118
SN - 9783319250861
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 332
EP - 338
BT - Similarity Search and Applications - 8th International Conference, SISAP 2015, Proceedings
A2 - Connor, Richard
A2 - Amato, Giuseppe
A2 - Falchi, Fabrizio
A2 - Gennaro, Claudio
PB - Springer Verlag
T2 - 8th International Conference on Similarity Search and Applications, SISAP 2015
Y2 - 12 October 2015 through 14 October 2015
ER -