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Computational Linguistics (CL) is an interdisciplinary field of research covering knowledge, mainly, from three areas: linguistics, computer science and mathematics (i Prat, 1994). It can be regarded in two respects: on the one side, the application of different techniques and outcomes from computer science to linguistics in order to investigate issues as how human beings acquire and produce language or, for instance, how language changes over time. On the other side, it could be defined as the application of linguistics rules and methods to computer science to devise practical engineering systems that involve the automatic processing of natural languages (Tsujii, 2011). The latter field of study is usually referred to as Natural Language Processing (NLP).
NLP research has focused on tasks such as machine translation (Wu et al., 2016; Koehn et al., 2007), information retrieval (Gysel et al., 2018; Borkar and Patil, 2013; Radwan et al., 2006), question answering (Xiong et al., 2016; Dong et al., 2015), sentiment Analysis (Severyn and Moschitti, 2015), topic modelling and text summarization. In the rest this section, we first introduce the problem of automatic text summarization, especially its extractive variant. Then, some concepts related to quantum-inspired evolutionary computing are provided.