Fast clustering algorithms for massive datasets

You gather tons of keywords over the Internet with a web crawler (crawling Wikipedia or DMOZ directories), and compute the frequencies for each keyword, and for each "keyword pair". A "keyword pair" is two keywords found on a same web page, or close to each other on a same web page. Also by keyword, I mean stuff like "California insurance", so a keyword usually contains more than one token, but rarely more than three. With all the frequencies, you can create a table (typically containing many million keywords, even after keyword cleaning), where each entry is a pair of keywords and 3 numbers, e.g.