Semantic Web != NLP + Agents. Atleast, not entirely!
There is an interesting article on CNet by Stefanie Olsen exploring what’s next on the VC horizon. The starting premise of the article (”its all about the data”) is obviously something that I enthusiastically embraced. But then, what followed did make me sigh.
“The first wave of Internet investing dealt with commercializing the Web, helping companies like Amazon.com and eBay get on their way. The second wave has been about helping people socialize and connect through sites like Flickr, YouTube, and Facebook. The third, venture capitalists say, will be about making sense of all the data people create around the Web, and then searching for patterns in the data to improve the delivery of personalized content, search results, or advertising.”
When you declare to a bunch of VC’s that you are a semantic web entrepreneur, the majority of them assume that you are involved in building technology to understand one of two things.
1. human language : process natural language(NLP) to help provide better web search(eg powerset) or better advertising (eg peer39)
2. human intent : analyse user activities such as searching and browsing and have “agents” go out and identify relevant information that can be pushed to the user (eg twine).
The pitch that these VC’s have heard a zillion times goes something like this - “Users are lazy. They are lazy producers of information and therefore we should understand what they are really saying. They are lazy consumers of information and therefore we should figure out what they really want and give it to them”.
It makes a great pitch. But unfortunately, it has been rather hard to deliver on that pitch. Powerset never seemed to take off. And RadarNetwork’s Twine, which hopes to be the poster boy of personalized content discovery, is yet to deliver on its promise.
Both these products attempt to use semantic web technologies to deliver value by exploiting the implicit semantics in information. However there is an alternative application of semweb technologies based on delivering value by exploiting the explicit semantics in information - value that could be in the form of improving content reuse, navigation and enduser procesability.
I for one believe that it’s the later that holds the greater promise for the near future. And that’s the belief upon which we are building our product here at OneBigWeb!
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PS : By explicit semantics, I am referring to content annotations that have been explicitly added by user. Mechanisms for doing so include microformats, rdfa and grddl.