Abstract
A semantic network is a graph which represents semantic relations between concepts, used in a lot of fields as a form of knowledge representation. This paper describes an automatic approach to identify semantic relations between concepts by using statistical information extracted from the Web. We automatically constructed an associative network starting from a lexicon. Moreover we applied these measures to the ESL semantic similarity test proving that our model is suitable for representing semantic correlations between terms obtaining an accuracy which is comparable with the state of the art.
This work has been supported by project PRISMA PON04a2 A/F funded by the Italian Ministry of University and Research within the PON 2007-2013 framework.
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Borzì, V., Faro, S., Pavone, A. (2014). Automatic Extraction of Semantic Relations by Using Web Statistical Information. In: Hernandez, N., Jäschke, R., Croitoru, M. (eds) Graph-Based Representation and Reasoning. ICCS 2014. Lecture Notes in Computer Science(), vol 8577. Springer, Cham. https://doi.org/10.1007/978-3-319-08389-6_15
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DOI: https://doi.org/10.1007/978-3-319-08389-6_15
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