After reading From Babel to Knowledge: Data Mining Large Digital Collections, by Dan Cohen, the idea of creating narrow search engines rather than using broad ones such as Google search, seems brilliant.  It was interesting to see how Cohen with the help of Google’s web search API was able to build a search engine that displayed classroom course material. He called it the Syllabus Finder.  Cohen said, “I thought a search engine that could locate syllabi on any topic would be useful for professors planning their next course, for discovering the kinds of books and assignments being commonly assigned, and for understanding the state of instruction more broadly.”  Assuming that professors would prefer to have their own search engine to look for class course work rather than web searching it, I couldn’t agree more with Dr. Cohen.

There are other similar search engines like Syllabus Finder.  One of them being the TIME Magazine Corpus.  The TIME Magazine Corpus has a record of all issues of TIME from 1923 – 2006 and allows users to search for words or phrases within all the text.  Although I find the Magazine Corpus to not be very user-friendly, it can still get the job done.  Rather than searching the the entire web for certain issues of TIME, this site can come in handy.

Another notable site is the Google books Ngram viewer, that let’s you search the use of certain words in books over a certain period of time.  The site shows a line graph representation of the popularity of certain words and even let’s you compare more than one of them on the same graph.  When putting in words such as ‘flavour’ and ‘flavor’ you can really see the comparison.  The graph shows that the spelling of the word in old English (flavour) went down periodically while the current version of the word (flavor) has gone up.

I find these sites to be very useful, enabling people to search for topics within a narrower search group, rather than a broader search area such as the web.