@inproceedings{d6d23eb8717b4230bc2ada5b512bc14d,
title = "Ranking vs. classification: A case study in mining organization name translation from snippets",
abstract = "Both classification and ranking strategy have been reported positively in mining the named entity (NE) translation from the snippets re-turned by the web search engine. Taking the most challenging issue of the organization name and its translation as an example, this paper conducts a contrastive study on the two strategies under SVM framework. We empirically show that the method of translation ranking achieves the best performance in various data settings, with the best Top-1 precision up to 65.75\%. We conclude that, compared with the classification strategy, the ranking strategy is more suitable in such snippet based translation mining, in which the unbalance data issue prevails.",
keywords = "Classification, Organization name translation, Ranking, SVM, Snippet mining",
author = "Muyun Yang and Zhenyong Shi and Sheng Li and Tiejun Zhao and Qi, \{Hao Liang\}",
year = "2009",
doi = "10.1109/IALP.2009.73",
language = "英语",
isbn = "9780769539041",
series = "2009 International Conference on Asian Language Processing: Recent Advances in Asian Language Processing, IALP 2009",
pages = "308--313",
booktitle = "2009 International Conference on Asian Language Processing",
note = "2009 International Conference on Asian Language Processing: Recent Advances in Asian Language Processing, IALP 2009 ; Conference date: 07-12-2009 Through 09-12-2009",
}