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Training speed and accuracy are two major concerns of large-scale natural language processing systems. Typically, we need to make a tradeoff between speed and accuracy. It is trivial to improve the tr...
Christian Jacquemin’s book Spotting and Discovering Terms through Natural Language Processing is a much needed and most welcome addition to the field of computational terminology. The central issue of...
The strong connection between knowledge representation and reasoning and natural language is the main theme of this book. The book is divided into two parts.Part I, consisting of five original or upda...
In 1993, Eugene Charniak published a slim volume entitledStatistical Language Learning. At the time, empirical techniques for natural language processing were on the rise; that year, Computational L...
Jurafsky and Martin’s long-awaited text sets a new gold standard that will be difficult to surpass, as attested by the flurry of glowing reviews that accompanied its publication early this year.1 In a...
This pap er is a review of some of the ma jor applications of nite-state transducers in natural-language pro cessing ranging from morphological analysis to nite-state parsing. The analysis and gener...
We describe the design and use of the Stanford CoreNLP toolkit, an extensible pipeline that provides core natural language analysis. This toolkit is quite widely used, both in the research NLP communi...
Recently there has been a rebirth of empiricism in the eld of natural language processing Manual encoding of linguistic information is being chal lenged by automated corpusbased learning as a method ...

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