Abstract
Semantic lexicons, such as Roget's Thesaurus or WordNet, act as useful knowledge resources in natural language processing applications. However, such manually created lexical resources do not always reflect the new terms and named entities frequently found in the Web. Moreover, manually maintaining lexical resources are costly and time consuming. Motivated by this challenge, we propose a method to automatically extract related terms using the web as a corpus. The proposed method exploits snippets retrieved from a web search engine and efficiently finds related terms.
