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Vowel Length From Latin to Romance

By Michele Loporcaro

This book "draws on extensive empirical data, including from lesser known varieties" and "puts forward a new account of a well-known diachronic phenomenon."


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Letter Writing and Language Change

Edited By Anita Auer, Daniel Schreier, and Richard J. Watts

This book "challenges the assumption that there is only one 'legitimate' and homogenous form of English or of any other language" and "supports the view of different/alternative histories of the English language and will appeal to readers who are skeptical of 'standard' language ideology."


Academic Paper


Title: Directional distributional similarity for lexical inference
Author: Lili Kolterman
Institution: Bar-Ilan University
Author: Ido Dagan
Institution: Bar-Ilan University
Author: Idan Szpektor
Institution: Yahoo! Research
Author: Maayan Zhitomirsky-Geffet
Institution: Bar-Ilan University
Linguistic Field: Semantics; Text/Corpus Linguistics
Abstract: Distributional word similarity is most commonly perceived as a symmetric relation. Yet, directional relations are abundant in lexical semantics and in many Natural Language Processing (NLP) settings that require lexical inference, making symmetric similarity measures less suitable for their identification. This paper investigates the nature of directional (asymmetric) similarity measures that aim to quantify distributional feature inclusion. We identify desired properties of such measures for lexical inference, specify a particular measure based on Average Precision that addresses these properties, and demonstrate the empirical benefit of directional measures for two different NLP datasets.

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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