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NEFUSI: A novel NEuroFUzzy approach for semantic SImilarity assessment

The challenge of determining the degree of semantic similarity between two expressions of a textual nature has become increasingly important in recent times. The great importance it has in many modern computing areas and the latest advances in neural computation have made the solutions better. NEFUSI (which stands for "NEuroFUzzy approach for semantic SImilarity assessment") aims to go a step further with the design and development of a novel neurofuzzy approach for semantic textual similarity based on neural networks and fuzzy logics. We intend to benefit from the outstanding capabilities of the latest neural models to work with text and, at the same time, from the possibilities that fuzzy logic offers to aggregate and decode numerical values in a personalized way. In this way, the project will build an approach intended to effectively determine the degree of semantic similarity of textual expressions with high accuracy in a wide range of scenarios concerning Search and Discovery.

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This project was funded through the NGI0 Discovery Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 825322.

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