Publishing Partner: Cambridge University Press CUP Extra Publisher Login
amazon logo
More Info


New from Oxford University Press!

ad

Speaking American: A History of English in the United States

By Richard W. Bailey

"Takes a novel approach to the history of American English by focusing on hotbeds of linguistic activity throughout American history."


New from Cambridge University Press!

ad

Language, Literacy, and Technology

By Richard Kern

"In this book, Richard Kern explores how technology matters to language and the ways in which we use it. Kern reveals how material, social and individual resources interact in the design of textual meaning, and how that interaction plays out across contexts of communication, different situations of technological mediation, and different moments in time."


Academic Paper


Title: Interpreting compound nouns with kernel methods
Author: Diarmuid Ó Séaghdha
Institution: Computer Laboratory, University of Cambridge, UK
Author: Ann Copestake
Email: click here TO access email
Homepage: http://www-csli.stanford.edu/~aac/
Institution: Stanford University
Linguistic Field: Computational Linguistics
Abstract: This paper presents a classification-based approach to noun–noun compound interpretation within the statistical learning framework of kernel methods. In this framework, the primary modelling task is to define measures of similarity between data items, formalised as kernel functions. We consider the different sources of information that are useful for understanding compounds and proceed to define kernels that compute similarity between compounds in terms of these sources. In particular, these kernels implement intuitive notions of lexical and relational similarity and can be computed using distributional information extracted from text corpora. We report performance on classification experiments with three semantic relation inventories at different levels of granularity, demonstrating in each case that combining lexical and relational information sources is beneficial and gives better performance than either source taken alone. The data used in our experiments are taken from general English text, but our methods are also applicable to other domains and potentially to other languages where noun–noun compounding is frequent and productive.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 19, Issue 3, which you can READ on Cambridge's site or on LINGUIST .



Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page