Potato I have

I found this interesting: there is a project to add semantics to MediaWiki, the software that runs Wikipedia and lots of other wikis. The goals page is clear and concise, and here’s a sample of the kind of stuff they want to enable. There is a background page touching on RDF/RDFS and OWL, and how semantic wiki is different from semantic web.

There’s a ton of information buried in wikis; semantic annotation would make it explicit and more directly usable. One challenge is doing this in a way that doesn’t cause usability problems — hopefully anyone who can handle wiki syntax can also handle the annotations.

(via rw)

The latest Economist Technology Quarterly (free access for the moment) has a brief status on video search. Searching the image itself is very difficult, but there is a lot of activity in searching associated text: the closed captions, the audio portion (via speech recognition), and human or machine produced video metadata.

IBM has a test version of a more sophisticated analysis/retrieval engine called Marvel; after manually tagging 1-5% of a set of video content, the system learns to recognize the rest — this is a huge reduction of the expensive, error-prone human tagging effort. IBM’s web has good detail on the project. From those pages I learned about MPEG-7, which is a video metadata (rather than encoding) standard.

The ETQ acknowledges that business models are lacking, but singles out Critical Mention as one that is working; they offer web-based search and alert (”reputation management”) services for TV news. I see in the news last week that they now have a licensing agreement with AP (Associated Press) Digital.

Since it looks like metadata is playing a big role in video search, it should be interesting to see which producers/consumers are doing the tagging, and where the analysis and search logic resides. The big search engines are an obvious home, fancy services like CM are another, but why shouldn’t I also have something to find stuff on my computer or LAN?

I’m probably mentioning Wikipedia too often, but my previous post about the semantic web offers an interesting comparison. The Forbes article and the Wikipedia entry are both approximately 1200 words, and the former is perhaps a better non-technical introduction, but I’m vastly more satisfied with the latter.

Why? The Wikipedia entry:

• has had an awful lot of editing, by many people
• has an ongoing discussion to improve the entry; anyone who can read the entry can participate
• being hypertext, directly links all of its numerous internal and external references
• also links its ‘Knowledge representation’ category, which has another 37 now 44 topically-related entries

The one is a feature article, the other an encyclopedia entry, they’re not the same thing, but it seems to me a good illustration of the different authoring processes and results.

This Forbes article describes the semantic web in simple terms, starting by mentioning how rudimentary our search technology is:

We’ve become a society of information managers, navigating huge amounts of data with ease and expertly tracking down obscure facts and figures.

But as far as we’ve come, all we’ve really done is become good at finding needles in haystacks.

Semantic web means smarter search, but that is just the start:

[S]emantic technology also holds great promise for all kinds of businesses. […] With data growth rates averaging between 20% and 30% annually, many businesses are drowning under the weight of their own files […] “We want to get the human out of the loop for obvious reasons–they cost money, and they make errors.”

So machines can handle a lot of the work in a rapid-growth area.

Google’s comparison shopper Froogle is given as an example of the first step to the semantic web: agreed-upon “tags” help us all find a price, for example, regardless of what language or what terms the web site uses. But it doesn’t do the harder things: relating terms and building context.

(via wired)