Computing Fuzzy Rough Set based Similarities with Fuzzy Inference and Its Application to Sentence Similarity Computations
This work addresses a specific issue in fuzzy set analysis for applications like sentence similarity, but appears incremental as it builds on existing Fuzzy Rough Set techniques.
The paper tackles the problem of combining lower and upper similarity measures from Fuzzy Rough Sets using a Fuzzy Inference Engine, and applies it to sentence similarity, achieving evaluation on the SICK2014 dataset.
Several research initiatives have been proposed for computing similarity between two Fuzzy Sets in analysis through Fuzzy Rough Sets. These techniques yield two measures viz. lower similarity and upper similarity. While in most applications only one entity is useful to further analysis and for drawing conclusions. The aim of this paper is to propose novel technique to combine Fuzzy Rough Set based lower similarity and upper similarity using Fuzzy Inference Engine. Further, the proposed approach is applied to the problem computing sentence similarity and have been evaluated on SICK2014 dataset.