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The literary imagination may take flight on the wings of metaphor,
but hard-headed scientists are just as likely as doe-eyed poets to
reach for a metaphor when the descriptive need arises. Metaphor is
a pervasive aspect of every genre of text and every register of
speech, and is as useful for describing the inner workings of a
"black hole" (itself a metaphor) as it is the affairs of the human
heart. The ubiquity of metaphor in natural language thus poses a
significant challenge for Natural Language Processing (NLP) systems
and their builders, who cannot afford to wait until the problems of
literal language have been solved before turning their attention to
figurative phenomena. This book offers a comprehensive approach to
the computational treatment of metaphor and its figurative
brethren-including simile, analogy, and conceptual blending-that
does not shy away from their important cognitive and philosophical
dimensions. Veale, Shutova, and Beigman Klebanov approach metaphor
from multiple computational perspectives, providing coverage of
both symbolic and statistical approaches to interpretation and
paraphrase generation, while also considering key contributions
from philosophy on what constitutes the "meaning" of a metaphor.
This book also surveys available metaphor corpora and discusses
protocols for metaphor annotation. Any reader with an interest in
metaphor, from beginning researchers to seasoned scholars, will
find this book to be an invaluable guide to what is a fascinating
linguistic phenomenon.
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 \ref{part5} closes
with summary and discussion. This book grew out of a week-long
course on automated evaluation of language production at the North
American Summer School for Logic, Language, and Information
(NASSLLI), attended by advanced undergraduates and early-stage
graduate students from a variety of disciplines. Teachers of
natural language processing, in particular, will find that the book
offers a useful foundation for a supplemental module on automated
scoring. Professionals and students in linguistics, applied
linguistics, educational technology, and other related disciplines
will also find the material here useful.
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