期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2006
卷号：2006
出版社：ACL Anthology
摘要：Web text has been successfully used as
training data for many NLP applications.
While most previous work accesses web
text through search engine hit counts, we
created a Web Corpus by downloading
web pages to create a topic-diverse collection
of 10 billion words of English. We
show that for context-sensitive spelling
correction the Web Corpus results are better
than using a search engine. For thesaurus
extraction, it achieved similar overall
results to a corpus of newspaper text.
With many more words available on the
web, better results can be obtained by collecting
much larger web corpora.
