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Words in Time and Place: Exploring Language Through the Historical Thesaurus of the Oxford English Dictionary

By David Crystal

Offers a unique view of the English language and its development, and includes witty commentary and anecdotes along the way.


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The Indo-European Controversy: Facts and Fallacies in Historical Linguistics

By Asya Pereltsvaig and Martin W. Lewis

This book "asserts that the origin and spread of languages must be examined primarily through the time-tested techniques of linguistic analysis, rather than those of evolutionary biology" and "defends traditional practices in historical linguistics while remaining open to new techniques, including computational methods" and "will appeal to readers interested in world history and world geography."


Academic Paper


Title: A non-negative tensor factorization model for selectional preference induction
Author: Tim Van De Cruys
Institution: Université Paris Diderot - Paris 7
Linguistic Field: Semantics; Text/Corpus Linguistics
Abstract: The distributional similarity methods have proven to be a valuable tool for the induction of semantic similarity. Until now, most algorithms use two-way co-occurrence data to compute the meaning of words. Co-occurrence frequencies, however, need not be pairwise. One can easily imagine situations where it is desirable to investigate co-occurrence frequencies of three modes and beyond. This paper will investigate tensor factorization methods to build a model of three-way co-occurrences. The approach is applied to the problem of selectional preference induction, and automatically evaluated in a pseudo-disambiguation task. The results show that tensor factorization, and non-negative tensor factorization in particular, is a promising tool for Natural Language Processing (nlp).

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 16, Issue 4, which you can READ on Cambridge's site .



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