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


New from Oxford University Press!

ad

The Language Hoax

By John H. McWhorter

The Language Hoax "argues that that all humans process life the same way, regardless of their language."


New from Cambridge University Press!

ad

Language and Development in Africa

By H. Ekkehard Wolff

Language and Development in Africa "discusses the resourcefulness of languages, both local and global, in view of the ongoing transformation of African societies as much as for economic development.. "


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: Exploiting the Wikipedia structure in local and global classification of taxonomic relations
Author: Quang Xuan Do
Institution: University of Illinois at Urbana-Champaign
Author: Dan Roth
Institution: University of Illinois at Urbana-Champaign
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: Determining whether two terms have an ancestor relation (e.g. Toyota Camry and car) or a sibling relation (e.g. Toyota and Honda) is an essential component of textual inference in Natural Language Processing applications such as Question Answering, Summarization, and Textual Entailment. Significant work has been done on developing knowledge sources that could support these tasks, but these resources usually suffer from low coverage, noise, and are inflexible when dealing with ambiguous and general terms that may not appear in any stationary resource, making their use as general purpose background knowledge resources difficult. In this paper, rather than building a hierarchical structure of concepts and relations, we describe an algorithmic approach that, given two terms, determines the taxonomic relation between them using a machine learning-based approach that makes use of existing resources. Moreover, we develop a global constraint-based inference process that leverages an existing knowledge base to enforce relational constraints among terms and thus improves the classifier predictions. Our experimental evaluation shows that our approach significantly outperforms other systems built upon the existing well-known knowledge sources.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 18, Issue 2, which you can READ on Cambridge's site .



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