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This book provides a corpus-led analysis of multi-word units (MWUs)
in English, specifically fixed pairs of nouns which are linked by a
conjunction, such as 'mum and dad', 'bride and groom' and 'law and
order'. Crucially, the occurrence pattern of such pairs is
dependent on genre, and this book aims to document the structural
distribution of some key Linked Noun Groups (LNGs). The author
looks at the usage patterns found in a range of poetry and fiction
dating from the 17th to 20th century, and also highlights the
important role such binomials play in academic English, while
acknowledging that they are far less common in casual spoken
English. His findings will be highly relevant to students and
scholars working in language teaching, stylistics, and language
technology (including AI).
This book explores the interconnections between linguistics and
Artificial Intelligence (AI) research, their mutually influential
theories and developments, and the areas where these two groups can
still learn from each other. It begins with a brief history of
artificial intelligence theories focusing on figures including Alan
Turing and M. Ross Quillian and the key concepts of priming,
spread-activation and the semantic web. The author details the
origins of the theory of lexical priming in early AI research and
how it can be used to explain structures of language that corpus
linguists have uncovered. He explores how the idea of mirroring the
mind's language processing has been adopted to create machines that
can be taught to listen and understand human speech in a way that
goes beyond a fixed set of commands. In doing so, he reveals how
the latest research into the semantic web and Natural Language
Processing has developed from its early roots. The book moves on to
describe how the technology has evolved with the adoption of
inference concepts, probabilistic grammar models, and deep neural
networks in order to fine-tune the latest language-processing and
translation tools. This engaging book offers thought-provoking
insights to corpus linguists, computational linguists and those
working in AI and NLP.
The highly frequent word items TO and OF are often conceived merely
as prepositions, carrying little meaning in themselves. This book
disputes that notion by analysing the usage patterns found for OF
and TO in different sets of text corpora.
This book shows that over forty years of psychological
laboratory-based research support the claims of the Lexical Priming
Theory. It examines how Lexical Priming applies to the use of
spoken English as the book provides evidence that Lexical Priming
is found in everyday spoken conversations.
Corpus Linguistics is becoming an increasingly important branch of
language research and interest has spread noticeably beyond the
confines of academia, fuelled by applications like text predicting
software. The idea of priming in language goes back to the early
1960s with the concept of a 'Teachable Language Comprehender',
which started experiments into language processing and which
inspired one of Google's chief engineers. The concept of Lexical
Priming (Hoey: 2005) aims to supply answers as to how we can
explain word choices and construction forms that are more frequent
than laws of probability would allow. This book provides a range of
arguments to support the validity of Lexical Priming as a
linguistic theory, while it also extends the reach of what Lexical
Priming has been used to describe. Beyond the written-text material
originally used, this book provides evidence that lexical priming
also applies to everyday spoken conversations as its psychological
foundations predict that it should.
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