Imagine you pick a news article at random and start counting the number of times a baseball player is mentioned by name. If one player is mentioned, it might be a cultural reference or a quote out of context. If two baseball players are mentioned by name, it’s possible that the it’s quoted dialogue between the two of them. But if three baseball players are named, then it’s getting likely that the article is in fact about baseball.
That’s the premise upon which Clumpy Bounce is based: if multiple people, places, or things relevant to a topic are mentioned on a Web page, it’s more likely that the page has something to do with that topic. Clumpy Bounce uses Wikipedia categories to make lists of popular pages within a category. It then builds Google queries based on the pages you pick from that list. Here’s how it works, in three steps:
1. Enter a keyword search (anything that might be in Wikipedia) and you’ll get a list of categories associated with that keyword.
2. Pick a category and you’ll get a list of checkboxes showing you the most recently-popular pages in that category.
3. Pick up to three and Clumpy Bounce will “clump” them into a Google search along with some cruft-reducing anti-search and “bounce” you to a new tab of Google search results.
The idea is to direct to rich, information-dense results in Google.
Try searching for company names, or plants, or minerals, or even fictional characters. Often you’ll see very famous people who end up at the top of categories with which you do not normally associate them. Don’t add those to your searches or you won’t get great results. If you don’t know anybody or anything on the page list you generate, pick a couple in the middle.
Try a search!
