I don't know about you, but I really like the way Amazon.com produces recommendations when I look at a book (or some music or shoes or a phone or...). It's pretty neat to see what people buy in addition to the item I'm looking at, even if I don't want to buy that item. All kinds of Web services offer recommendations. Netflix even held a contest for people to improve the company's movie recommendations. With all these automated suggestions floating around, have you ever wished that there could be some for your research?
After you get back from your July 4th holiday weekend, the Get It menu will look just a little different. Oh, it will still take you from citation to full text, catalog search, or interlibrary loan in just a few clicks. But it will also make recommendations. Based on the article you're trying to get, Get It can suggest more articles on that same topic. It will give you a full citation and the Get It button. Like the look of one of those articles? Click the Get It button to - well - get it. You'll also be able to export those suggested article citations to RefWorks or Zotero.
How does Get It know what to recommend? The software is based on research done at Los Alamos National Laboratory. Basically, the researchers were trying to turn some of libraries' ordinary usage data into value-added services. The recommender service gathers up data from many libraries to inform its recommendations. Suppose you're researching food safety and find three or four articles really relevant to your specific topic. You might recommend those articles to a friend who's researching the same thing. Now spread that out over hundreds or thousands of food safety researchers, all of whom found the same three or ten or twenty articles clustering around that topic. In the same way that Amazon.com turns data about customer purchases into recommendations, Get It's service will turn all that food safety research into suggestions for you.
Or, if you like neat and tidy summaries, you can think of it this way:
Usage creates relationships; relationships create recommendations.