Word Sense Discrimination on Tweets: A Graph-based Approach

Flavio Massimiliano Cecchini, Elisabetta Fersini, Enza Messina

2015

Abstract

In this paper we are going to detail an unsupervised, graph-based approach for word sense discrimination on tweets. We deal with this problem by constructing a word graph of co-occurrences. By defining a distance on this graph, we obtain a word metric space, on which we can apply an aggregative algorithm for word clustering. As a result, we will get word clusters representing contexts that discriminate the possible senses of a term. We present some experimental results both on a data set consisting of tweets we collected and on the data set of task 14 at SemEval-2010.

Paper Citation

in Harvard Style

Cecchini F., Fersini E. and Messina E. (2015). Word Sense Discrimination on Tweets: A Graph-based Approach . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 138-146. DOI: 10.5220/0005640501380146

in Bibtex Style

@conference{kdir15,
author={Flavio Massimiliano Cecchini and Elisabetta Fersini and Enza Messina},
title={Word Sense Discrimination on Tweets: A Graph-based Approach},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={138-146},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005640501380146},
isbn={978-989-758-158-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - Word Sense Discrimination on Tweets: A Graph-based Approach
SN - 978-989-758-158-8
AU - Cecchini F.
AU - Fersini E.
AU - Messina E.
PY - 2015
SP - 138
EP - 146
DO - 10.5220/0005640501380146