Type of Engine: Visual and clustering.
Overall: Good.
If this engine were a drink it would be…an Emu Export, it’s Australian, has a funny name, I’d never heard of it until very recently, and it’s a safe bet that you’ve never heard of it.

Mooter is a visual clustering search engine and I like it. They’re from Australia and have been live only about a year.

According to their Technology site, which actually provides some useful information about what they’re up to, “Mooter gets it results from its own spidering, and a unique index of websites. While we are growing, we are supplementing our index with metasearch, and comparing the results from various engines before applying our analysis algorithms.” This is an interesting statement and I’m not exactly sure what they mean by it. If I had to guess it sounds like they’re spidering other engines’ indexes to create their clusters. Is this different from what Clusty or Clush does? I’m not sure, but would love to know the answer. Please email me if you know. It sounds like they plan to generate an entire web index, but that could be wishful thinking.

UI and Features
For the most part I like their interface, it’s simple and almost cheesy, but somehow likable. The Overture supplied Sponsored Links are killing me though. When you click into a cluster, the Sponsored Links take up nearly half the screen; bad, very bad.

You can click “All Results” to get the full list of results. Mooter maxes out at 120 results, or at least I didn’t find any queries that produced more than that.

If you don’t like the first cluster you see, click on the “Next Clusters” icon (the icon needs some improvement; it looks like a cluster of red pimples) to see another cluster.

Query Example
For phrase searches, each word usually becomes a cluster. For the search “William Styron” one of the clusters was “William.” Not good, but then I clicked on the cluster link and the sites were indeed about William Styron, and not just any old William. But still a “William” cluster doesn’t really help me.

Even if the name of a cluster doesn’t sound relevant, the links contained therein were generally on target. So I’d say they’re getting the back-end organization of clusters correct, but what they need to do is improve their cluster names and concepts. Maybe more phrase matching rather than pulling out just single terms, as if I know what I’m talking about.

They could also make the visual part of their results more compelling. As it is right now, it almost doesn’t need to be visual because the visual part of it doesn’t add much beyond novelty (and even the novelty is wearing off as more Kartoo-style visual engines appear).