Abstract
The Semantic Textual Similarity (STS) task aims capturing a bidirectional-graded equivalence between the pair of short texts. This work proposes a STS measure for the Portuguese Language based on Semantic Inferentialism Model (SIM) and InferenceNet.BR. We argue that the expression of inferential, causal, motivational and encyclopedic content of InferenceNet enables a more robust and efficient model for the STS task. An extrinsic evaluation in a Portuguese-language processing application - a Case-Based Reasoning system for Requirements Engineering - provided real scenario to assess how the proposed STS measure contributes to the effectiveness of NLP applications.
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Pinheiro, V., Furtado, V., Albuquerque, A. (2014). Semantic Textual Similarity of Portuguese-Language Texts: An Approach Based on the Semantic Inferentialism Model. In: Baptista, J., Mamede, N., Candeias, S., Paraboni, I., Pardo, T.A.S., Volpe Nunes, M.d.G. (eds) Computational Processing of the Portuguese Language. PROPOR 2014. Lecture Notes in Computer Science(), vol 8775. Springer, Cham. https://doi.org/10.1007/978-3-319-09761-9_19
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DOI: https://doi.org/10.1007/978-3-319-09761-9_19
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