Difference between revisions of "Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia"
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| + | | title = Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia | ||
| + | | date = 2008 | ||
| + | | authors = [[Jong-Hoon Oh]]<br />[[Daisuke Kawahara]]<br />[[Kiyotaka Uchimoto]]<br />[[Jun’ichi Kazama]]<br />[[Kentaro Torisawa]] | ||
| + | | doi = 10.1109/WIIAT.2008.317 | ||
| + | | link = http://dl.acm.org/citation.cfm?id=1486927.1487058 | ||
| + | }} | ||
'''Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2008, written by [[Jong-Hoon Oh]], [[Daisuke Kawahara]], [[Kiyotaka Uchimoto]], [[Jun’ichi Kazama]] and [[Kentaro Torisawa]]. | '''Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2008, written by [[Jong-Hoon Oh]], [[Daisuke Kawahara]], [[Kiyotaka Uchimoto]], [[Jun’ichi Kazama]] and [[Kentaro Torisawa]]. | ||
== Overview == | == Overview == | ||
Authors present a novel method for discovering missing cross-language links between English and Japanese [[Wikipedia]] articles. Authors collect candidates of missing cross-language links -- a pair of English and Japanese Wikipedia articles, which could be connected by cross-language links. Then authors select the correct cross-language links among the candidates by using a classifier trained with various types of [[features]]. Authors method has three desirable characteristics for discovering missing links. First, method can discover cross-language links with high accuracy (92% precision with 78% recall rates). Second, the features used in a classifier are language-independent. Third, without relying on any external knowledge, authors generate the features based on resources automatically obtained from Wikipedia. In this work, authors discover approximately $10^5$ missing cross-language links from Wikipedia, which are almost two-thirds as many as the existing cross-language links in Wikipedia. | Authors present a novel method for discovering missing cross-language links between English and Japanese [[Wikipedia]] articles. Authors collect candidates of missing cross-language links -- a pair of English and Japanese Wikipedia articles, which could be connected by cross-language links. Then authors select the correct cross-language links among the candidates by using a classifier trained with various types of [[features]]. Authors method has three desirable characteristics for discovering missing links. First, method can discover cross-language links with high accuracy (92% precision with 78% recall rates). Second, the features used in a classifier are language-independent. Third, without relying on any external knowledge, authors generate the features based on resources automatically obtained from Wikipedia. In this work, authors discover approximately $10^5$ missing cross-language links from Wikipedia, which are almost two-thirds as many as the existing cross-language links in Wikipedia. | ||
Revision as of 08:32, 13 February 2021
Authors | Jong-Hoon Oh Daisuke Kawahara Kiyotaka Uchimoto Jun’ichi Kazama Kentaro Torisawa |
|---|---|
Publication date | 2008 |
DOI | 10.1109/WIIAT.2008.317 |
Links | Original |
Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia - scientific work related to Wikipedia quality published in 2008, written by Jong-Hoon Oh, Daisuke Kawahara, Kiyotaka Uchimoto, Jun’ichi Kazama and Kentaro Torisawa.
Overview
Authors present a novel method for discovering missing cross-language links between English and Japanese Wikipedia articles. Authors collect candidates of missing cross-language links -- a pair of English and Japanese Wikipedia articles, which could be connected by cross-language links. Then authors select the correct cross-language links among the candidates by using a classifier trained with various types of features. Authors method has three desirable characteristics for discovering missing links. First, method can discover cross-language links with high accuracy (92% precision with 78% recall rates). Second, the features used in a classifier are language-independent. Third, without relying on any external knowledge, authors generate the features based on resources automatically obtained from Wikipedia. In this work, authors discover approximately $10^5$ missing cross-language links from Wikipedia, which are almost two-thirds as many as the existing cross-language links in Wikipedia.
