Using WordNet-based context vectors to estimate the semantic relatedness of concepts
S. Patwardhan, and T. Pedersen. Proceedings of the EACL 2006 Workshop Making Sense of Sense-Bringing Computational Linguistics and Psycholinguistics Together, 1501, page 1--8. (2006)
basically only incorporates a second-order-coocc of vectors built by WordNet glosses. Evaluation is pretty weak, to the point where some numbers aren't even explained. Evaluation was carried out on M&C dataset (30 pairs), which is REALLY weak.
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%0 Conference Paper
%1 patwardhan2006using
%A Patwardhan, Siddharth
%A Pedersen, Ted
%B Proceedings of the EACL 2006 Workshop Making Sense of Sense-Bringing Computational Linguistics and Psycholinguistics Together
%D 2006
%K
%P 1--8
%T Using WordNet-based context vectors to estimate the semantic relatedness of concepts
%V 1501
@inproceedings{patwardhan2006using,
added-at = {2013-09-02T13:38:03.000+0200},
author = {Patwardhan, Siddharth and Pedersen, Ted},
biburl = {https://www.bibsonomy.org/bibtex/22c5dbbd11740d29d12918a3aa8772c23/thoni},
booktitle = {Proceedings of the EACL 2006 Workshop Making Sense of Sense-Bringing Computational Linguistics and Psycholinguistics Together},
interhash = {16a0a4c8ba8ddf4136b59065eb7d2e1d},
intrahash = {2c5dbbd11740d29d12918a3aa8772c23},
keywords = {},
pages = {1--8},
timestamp = {2013-09-02T13:38:03.000+0200},
title = {Using WordNet-based context vectors to estimate the semantic relatedness of concepts},
volume = 1501,
year = 2006
}