@conference{168,
title = {A Comparative Analysis of Network-Based Similarity Measures for Scientific Paper Recommendations},
author = {Laura Steinert and H.Ulrich Hoppe},
abstract = {In this paper three similarity measures for scientific papers are compared: bibliographic coupling, co-citation coupling and cosine similarity. All three measures are based on the connections of papers in citation networks. The comparison is conducted both on a mathematical as well as an empirical level. The latter is performed on a real citation network as well as artificially generated networks. The mathematical comparison shows that some measures are structurally very similar, yet if node pairs are ordered according to their similarity, the two measures do not always produce the same rankings. The empirical evaluation shows that bibliographic coupling and one variant of cosine similarity tend to produce the same rankings. The same holds for co-citation coupling and another variant of cosine similarity. Therefore, if only rankings are considered, these measures are interchangeable. The rankings produced by co-citation coupling and bibliographic coupling on the other hand are very different. This also applies to the two cosine similarity variants. Therefore, these measures are not interchangeable.},
year = {2016},
journal = {Network Intelligence Conference (ENIC), 2016 Third European},
month = { 02 February 2017 },
publisher = { IEEE },
address = {Wroclaw, Poland },
isbn = { Electronic ISBN: 978-1-5090-3455-0 Print on Demand(PoD) ISBN: 978-1-5090-3456-7 },
doi = { 10.1109/ENIC.2016.011},
}