| 书目名称 | Cognitively Inspired Natural Language Processing | | 副标题 | An Investigation Bas | | 编辑 | Abhijit Mishra,Pushpak Bhattacharyya | | 视频video | | | 概述 | The first of its kind book, shedding new light on how modern Natural Language Processing (NLP) systems can leverage human cognitive data.Includes the authors’ research contributions that are “relevant | | 丛书名称 | Cognitive Intelligence and Robotics | | 图书封面 |  | | 描述 | .This book shows ways of augmenting the capabilities of Natural Language Processing (NLP) systems by means of cognitive-mode language processing. The authors employ eye-tracking technology to record and analyze shallow cognitive information in the form of gaze patterns of readers/annotators who perform language processing tasks. The insights gained from such measures are subsequently translated into systems that help us (1) assess the actual cognitive load in text annotation, with resulting increase in human text-annotation efficiency, and (2) extract cognitive features that, when added to traditional features, can improve the accuracy of text classifiers. In sum, the authors’ work successfully demonstrates that cognitive information gleaned from human eye-movement data can benefit modern NLP. ..Currently available Natural Language Processing (NLP) systems are weak AI systems: they seek to capture the functionality of human language processing, without worrying about how thisprocessing is realized in human beings’ hardware. In other words, these systems are oblivious to the actual cognitive processes involved in human language processing. This ignorance, however, is NOT bliss! The | | 出版日期 | Book 2018 | | 关键词 | Eye-tracking and NLP; Cognitive NLP; Cognitive Computational Linguistics; Eye-movement Data for NLP; Cog | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-13-1516-9 | | isbn_softcover | 978-981-13-4643-9 | | isbn_ebook | 978-981-13-1516-9Series ISSN 2520-1956 Series E-ISSN 2520-1964 | | issn_series | 2520-1956 | | copyright | Springer Nature Singapore Pte Ltd. 2018 |
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发表于 2025-3-21 16:51:44
