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A syntactic approach for searching similarities within sentences


Federica Mandreoli, Riccardo Martoglia, and Paolo Tiberio

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Abstract

Textual data is the main electronic form of knowledge representation. Sentences, meant as logic units of meaningful word sequences, can be considered its backbone. In this paper, we propose a solution based on a purely syntactic approach for searching similarities within sentences, named approximate sub2sequence matching. This process being very time consuming, efficiency in retrieving the most similar parts available in large repositories of textual data is ensured by making use of new filtering techniques. As far as the design of the system is concerned, we chose a solution that allows us to deploy approximate sub2 sequence matching without changing the underlying database.


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