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


New from Oxford University Press!

ad

Linguistic Diversity and Social Justice

By Ingrid Piller

Linguistic Diversity and Social Justice "prompts thinking about linguistic disadvantage as a form of structural disadvantage that needs to be recognized and taken seriously."


New from Cambridge University Press!

ad

Language Evolution: The Windows Approach

By Rudolf Botha

Language Evolution: The Windows Approach addresses the question: "How can we unravel the evolution of language, given that there is no direct evidence about it?"


The LINGUIST List is dedicated to providing information on language and language analysis, and to providing the discipline of linguistics with the infrastructure necessary to function in the digital world. LINGUIST is a free resource, run by linguistics students and faculty, and supported primarily by your donations. Please support LINGUIST List during the 2016 Fund Drive.

Academic Paper


Title: WordICA—emergence of linguistic representations for words by independent component analysis
Author: Timo Honkela
Institution: Aalto University School of Science and Technology
Author: Aapo Hyvärinen
Institution: University of Helsinki
Author: Jaako J Väyrynen
Institution: Aalto University School of Science and Technology
Linguistic Field: Applied Linguistics; Computational Linguistics; Text/Corpus Linguistics
Abstract: We explore the use of independent component analysis (ICA) for the automatic extraction of linguistic roles or features of words. The extraction is based on the unsupervised analysis of text corpora. We contrast ICA with singular value decomposition (SVD), widely used in statistical text analysis, in general, and specifically in latent semantic analysis (LSA). However, the representations found using the SVD analysis cannot easily be interpreted by humans. In contrast, ICA applied on word context data gives distinct features which reflect linguistic categories. In this paper, we provide justification for our approach called WordICA, present the WordICA method in detail, compare the obtained results with traditional linguistic categories and with the results achieved using an SVD-based method, and discuss the use of the method in practical natural language engineering solutions such as machine translation systems. As the WordICA method is based on unsupervised learning and thus provides a general means for efficient knowledge acquisition, we foresee that the approach has a clear potential for practical applications.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 16, 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