TY - JOUR
T1 - Similarity computation using semantic networks created from web-harvested data
AU - Iosif, Elias
AU - Potamianos, Alexandros
N1 - Publisher Copyright:
© 2013 Cambridge University Press.
PY - 2015/1/23
Y1 - 2015/1/23
N2 - We investigate language-agnostic algorithms for the construction of unsupervised distributional semantic models using web-harvested corpora. Specifically, a corpus is created from web document snippets, and the relevant semantic similarity statistics are encoded in a semantic network. We propose the notion of semantic neighborhoods that are defined using co-occurrence or context similarity features. Three neighborhood-based similarity metrics are proposed, motivated by the hypotheses of attributional and maximum sense similarity. The proposed metrics are evaluated against human similarity ratings achieving state-of-the-art results.
AB - We investigate language-agnostic algorithms for the construction of unsupervised distributional semantic models using web-harvested corpora. Specifically, a corpus is created from web document snippets, and the relevant semantic similarity statistics are encoded in a semantic network. We propose the notion of semantic neighborhoods that are defined using co-occurrence or context similarity features. Three neighborhood-based similarity metrics are proposed, motivated by the hypotheses of attributional and maximum sense similarity. The proposed metrics are evaluated against human similarity ratings achieving state-of-the-art results.
UR - http://www.scopus.com/inward/record.url?scp=84919781939&partnerID=8YFLogxK
U2 - 10.1017/S1351324913000144
DO - 10.1017/S1351324913000144
M3 - Article
AN - SCOPUS:84919781939
SN - 1351-3249
VL - 21
SP - 49
EP - 79
JO - Natural Language Engineering
JF - Natural Language Engineering
IS - 1
ER -