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Jost Gippert: Our Featured Linguist!

"Buenos dias", "buenas noches" -- this was the first words in a foreign language I heard in my life, as a three-year old boy growing up in developing post-war Western Germany, where the first gastarbeiters had arrived from Spain. Fascinated by the strange sounds, I tried to get to know some more languages, the only opportunity being TV courses of English and French -- there was no foreign language education for pre-teen school children in Germany yet in those days. Read more



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What is English? And Why Should We Care?

By: Tim William Machan

To find some answers Tim Machan explores the language's present and past, and looks ahead to its futures among the one and a half billion people who speak it. His search is fascinating and important, for definitions of English have influenced education and law in many countries and helped shape the identities of those who live in them.


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Medical Writing in Early Modern English

Edited by Irma Taavitsainen and Paivi Pahta

This volume provides a new perspective on the evolution of the special language of medicine, based on the electronic corpus of Early Modern English Medical Texts, containing over two million words of medical writing from 1500 to 1700.


Academic Paper


Title: Modeling Word Senses with Fuzzy Clustering
Paper URL: http://wo.uio.no/as/WebObjects/theses.woa/wo/2.3.9
Author: Erik Velldal
Email: click here to access email
Institution: University of Oslo
Linguistic Field: Computational Linguistics; Language Acquisition; Semantics; Text/Corpus Linguistics
Abstract: This thesis describes a clustering approach to automatically inferring soft semantic classes and characterizing senses of a set of Norwegian nouns. The words are represented by way of their distribution in text, identified as local contexts in the form of lexical-syntactic relations. Through a shallow processing step the context features are extracted for lemmatized word forms in syntactically tagged corpora. The corresponding frequency counts of noun-context co-occurrences are weighted with a statistical association measure, and the distributional profile of a given word is represented in the form of a feature vector in a semantic space model. A hybrid approach is taken when clustering the word vectors; a bottom-up hierarchical method is used to initialize various types of fuzzy partitional clusterings. With the purpose of capturing the notion of typicality the clusters are construed as fuzzy sets, and the words are assigned varying degrees of membership with respect to the various classes. Words are assigned graded memberships in clusters on the basis of their resemblance towards a class prototype. The goal is to automatically uncover semantic classes, where the various memberships of a given word in these fuzzy clusters can be used to characterize its various senses.
Type: Individual Paper
Status: Completed
URL: http://wo.uio.no/as/WebObjects/theses.woa/wo/2.3.9


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