Titlebook: Cognitively Inspired Natural Language Processing; An Investigation Bas Abhijit Mishra,Pushpak Bhattacharyya Book 2018 Springer Nature Singa

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Cognitively Inspired Natural Language Processing978-981-13-1516-9Series ISSN 2520-1956 Series E-ISSN 2520-1964

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https://doi.org/10.1007/978-3-662-53620-9on complexity for translation and sentiment annotation. We realize, gaze data, a form of . can be useful for labeling training data with . scores, when manually assigning such labels becomes extremely difficult due to its highly subjective nature. We rather rely on simplistic gaze-based measures lik

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MgO: Melting Curve, Melting Temperature,assification. We discuss several possibilities of extracting features from the eye-movement patterns of annotators and injecting them in popular NLP frameworks. We show that features derived from such forms of cognitive data (referred to as . or .), when augmented with traditional linguistic feature

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MgO: Melting Curve, Melting Temperature,m eye-movement patterns, EEG signals, brain imaging, etc. Such extraction of features has been typically manual, as we have seen in the previous chapter. We now contend that manual extraction of features is not good enough to tackle text subtleties that characteristically prevail in complex classifi

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https://doi.org/10.1007/978-981-13-1516-9Eye-tracking and NLP; Cognitive NLP; Cognitive Computational Linguistics; Eye-movement Data for NLP; Cog