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1. Alex Iskold - October 29, 2007

Hi Jeremy,

I agree that narrow solutions are going to win, at least in the long term and I think that this is a good thing. If we start with the goal of annotating entire body of the web with semantics we are stuck with Herculian task.

Taking a step back and thinking what is actually useful, leads us away and into the verticals: books, movies, stocks, recipes, restaurants, people, companies, countries – the basic stuff.

So, as you are pointing out, we can solve these simpler problems first, deliver end user value, learn a ton from our mistakes, and then iterate to a broader solution.

2. Meaning = Data + Structure « Lightspeed Venture Partners Blog - October 29, 2007

[...] User generated structure 2. Inferring structure from knowledge of the domain 3. Inferring structure from user [...]

3. mathew johnson - October 29, 2007

Hi Jeremy,

You characterize the chicken and egg problem of building apps with enough day 1 me-value to encourage people to start adding the meta information that will ultimately benefit the network of users.

One way we are looking at things at blist is amplifying the small and precious amount of UGC structure that you are able to generate and syndicating it out to similar data elsewhere.

As is abundantly clear to everyone, the velocity of new structure creation is much lower than the velocity of new content creation, and so it’s vital to build the the biggest multiplier possible to catch structure up to data.

Mathew Johnson

4. Jud Valeski - October 31, 2007

What a fun series of posts. Thanks for putting the energy into these! UGS is a fascinating topic and I was compelled to describe how my company, Me.dium, is approaching the problem with a blend of the human mind and machines.

In short, asking users to do anything, as you point out, is a major uphill battle. Machines aren’t smart enough to do what our brains can do, so me.dium is passively leveraging the human mind, our behaviors, and content to get people the information they seek.

I go into more detail in my blog post at http://me.dium.com/node/1026

5. mike simonsen - November 3, 2007

Love the orienteering metaphor. I’d extend it to the ontology itself. The really useful applications are driven by people orienteering their way through the structure as well. It turns out in practice that human-powered domain expertise is required to get the thing off the ground.

if you retitled the post as “Value = data + structure” (where meaning implies value), and the data portion of the equation is the given (UG or otherwise), then structure is the value add. That’s the secret sauce. And it doesn’t come from automated semantic recognition. It comes from application design insight and sparks of great marketing.

Further, in this vertical world, domain expertise is critical for monetization (value begets revenue). Because the money answers aren’t self-evident in the data. Automating semantic analysis to /discover/ meaning is like automating mining before you know there’s value in diamonds. You can find X, Y, and Z minerals, their relationships to one another, their mass, and composition. But you can’t infer that my fiancee doesn’t want to put a chunk of quartz on her finger.

It turns out to be self reinforcing too. You get customers in the vertical, they ask really smart questions that you never thought about and you go create the structure to discover the answers in the data.

The framework looks something like this:
expertise -> ontology -> data -> meaning -> repeat.

To invert that process is really bad science ;-) You don’t create the hypothesis to fit the data, you hypothesize first.

But we all start out with the grand visions of cross domain applications. Then you wake up one day and your elegant open platform has transformed into this rigid, structured beast that knows only movies, or people, or in our case real estate. Then you lean back and catch a few more z’s secure in the fact that same platform is making you money.

Or maybe that’s entirely your point here…

6. mylaine - November 15, 2007

Love the orienteering metaphor. I’d extend it to the ontology itself. The really useful applications are driven by people orienteering their way through the structure as well. It turns out in practice that human-powered domain expertise is required to get the thing off the ground.

if you retitled the post as “Value = data + structure” (where meaning implies value), and the data portion of the equation is the given (UG or otherwise), then structure is the value add. That’s the secret sauce. And it doesn’t come from automated semantic recognition. It comes from application design insight and sparks of great marketing.

Further, in this vertical world, domain expertise is critical for monetization (value begets revenue). Because the money answers aren’t self-evident in the data. Automating semantic analysis to /discover/ meaning is like automating mining before you know there’s value in diamonds. You can find X, Y, and Z minerals, their relationships to one another, their mass, and composition. But you can’t infer that my fiancee

7. Meaning = data + Structure: More thoughts on user generated structure « Lightspeed Venture Partners Blog - November 24, 2007

[...] Related post on inferring structure from domain knowledge now [...]

8. VentureBeat » Predictions for the consumer internet in 2008 - December 3, 2007

[...] the user experience. This will include both explicit (user-generated structure) and implicit (inferring structure from domain knowledge or user behavior) [...]

9. 2008 Consumer Internet Predictions « Lightspeed Venture Partners Blog - December 5, 2007

[...] the user experience. This will include both explicit (user-generated structure) and implicit (inferring structure from domain knowledge or user behavior) [...]

10. 網絡集錦 « Alan Poon’s Blog - February 24, 2008

[...] 網絡集錦網絡集錦網絡集錦核能發電回春?想出來的人正豬頭﹗R.I.P. x 2 / [...]

11. Semantic web in travel « Lightspeed Venture Partners Blog - February 26, 2008

[...] the past, I am a believer in approaching the semantic web bottom up rather than top down, i.e. by inferring structure from domain knowledge rather than requiring all websites to mark up their content in RDF. The user doesn’t care [...]

12. Innovablog > Le Web Sémantique : Où sont les outils de création de contenu riche ? - February 26, 2008

[...] Web Sémantique : Meaning = Data + Structure, basé sur une structure créée par l’individu ; le domaine du savoir ainsi que le comportement de l’utilisateur, qui se focalisent eux sur le problème de la [...]

13. Kango Blog » Blog Archive » The Blogosphere Speaks Out About Kango-A Wrap Up - March 26, 2008

[...] “I am a believer in approaching the semantic web top down rather than bottom up, i.e. by inferring structure from domain knowledge rather than requiring all websites to mark up their content in RDF.” He subsequently pointed [...]

14. elda - June 14, 2008

Hi Jeremy
I stumbled upon this website and thought I that I would like to let you know that there is a startup that does this, introducing structure in the data that users generate.
Check out http://www.tablefy.com, the founder meticulously micro blog his progress in promoting it, perhaps you can help him?

https://twitter.com/tablefy

here is a visual tour of the site: http://www.tablefy.com/pages/tour

15. elda - June 14, 2008

argh i accidentally pressed post,
i was gonna say, the data that the users generate in tablefy.com is inherently structured in a tabular way. Some call it data sheets, some comparison table but whatever it is, the structure is there.

Enjoy

16. travelosity - June 23, 2009

looking for flight deals offers from newyork to chaicago, i have found this website very intersting with great offers


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