2012 BootstrappedLanguageIdentificat

• (Mayer, 2012) ⇒ Uwe F. Mayer. (2012). “Bootstrapped Language Identification for Multi-site Internet Domains.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339622

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222012%22+Bootstrapped+Language+Identification+for+Multi-site+Internet+Domains
• http://dl.acm.org/citation.cfm?id=2339530.2339622&preflayout=flat#citedby

Quotes

Author Keywords

• Boosting; language identification; large data; natural language processing; statistical model

Abstract

We present an algorithm for language identification, in particular of short documents, for the case of an Internet domain with sites in multiple countries with differing languages. The algorithm is significantly faster than standard language identification methods, while providing state-of-the-artidentification. We bootstrap the algorithm based on the language identification based on the site alone, a methodology suitable for any supervised language identification algorithm. We demonstrate the bootstrapping and algorithm on eBay email data and on Twitter status updates data. The algorithm is deployed at eBay as part of the back-office development data repository.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 BootstrappedLanguageIdentificat	Uwe F. Mayer			Bootstrapped Language Identification for Multi-site Internet Domains				10.1145/2339530.2339622		2012