JU-Evora: A graph based cross-level semantic similarity analysis using discourse information
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ACL
Abstract
Text Analytics using semantic information is
the latest trend of research due to its potential
to represent better the texts content compared
with the bag-of-words approaches. On the
contrary, representation of semantics through
graphs has several advantages over the tradi-
tional representation of feature vector. There-
fore, error tolerant graph matching techniques
can be used for text comparison. Neverthe-
less, not many methodologies exist in the lit-
erature which expresses semantic representa-
tions through graphs. The present system is
designed to deal with cross level semantic
similarity analysis as proposed in the
SemEval-2014 : Semantic Evaluation, Inter-
national Workshop on Semantic Evaluation,
Dublin, Ireland.