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Titlebook: Automated Essay Scoring; Beata Beigman Klebanov,Nitin Madnani Book 2022 Springer Nature Switzerland AG 2022

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发表于 2025-3-21 17:17:30 | 显示全部楼层 |阅读模式
期刊全称Automated Essay Scoring
影响因子2023Beata Beigman Klebanov,Nitin Madnani
视频videohttp://file.papertrans.cn/167/166291/166291.mp4
学科分类Synthesis Lectures on Human Language Technologies
图书封面Titlebook: Automated Essay Scoring;  Beata Beigman Klebanov,Nitin Madnani Book 2022 Springer Nature Switzerland AG 2022
影响因子This book discusses the state of the art of automated essay scoring, its challenges and its potential. One of the earliest applications of artificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developments in this field against the backdrop of Elias Page‘s seminal 1966 paper titled "The Imminence of Grading Essays by Computer." Part 1 establishes what automated essay scoring is about, why it exists, where the technology stands, and what are some of the main issues. In Part 2, the book presents guided exercises to illustrate how one would go about building and evaluating a simple automated scoring system, while Part 3 offers readers a survey of the literature on different types of scoring models, the aspects of essay quality studied in prior research,and the implementation and evaluation of a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part ef{part5} closes with summary and discussion. This bo
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1947-4040 a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part ef{part5} closes with summary and discussion. This bo978-3-031-01054-5978-3-031-02182-4Series ISSN 1947-4040 Series E-ISSN 1947-4059
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1947-4040 rtificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developm
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Genre- and Task-Specific Featuressummarization. The extent of variation in the tasks we review here, as well as in approaches developed for capturing task-specific elements, suggests clearly that assessment of writing is not a one-size-fits-all kind of endeavor.
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Looking Back, Looking Aheadw far the field has come, against the backdrop of the expectations and the hurdles laid out in that paper. The discussion in this chapter draws heavily on the theme paper on automated essay scoring presented by the authors at the 2020 meeting of the Association for Computational Linguistics (Beigman Klebanov & Madnani, 2020).
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978-3-031-01054-5Springer Nature Switzerland AG 2022
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