Contributions on semantic similarity and its applications to data privacy

Abstract

Semantic similarity aims at quantifying the resemblance between the meaning of textual terms. Thus, it represents the corner stone of textual understanding. Given the increasing availability and importance of textual sources within the current context of Information Societies, a lot of attention has been put in recent years in the development of mechanisms to automatically measure semantic similarity and to apply them to tasks dealing with textual inputs (e.g. document classification, information retrieval, question answering, privacy-protection, etc.). This chapter offers describes and discusses recent findings and proposals published by the authors on semantic similarity. Moreover, it also details recent works applying semantic similarity to privacy protection of textual data.