Archive for May, 2008

LinkedIn on the semantic web and the Semantic Web

May 16, 2008

SemanticReport has done a great blog post on how LinkedIn is using microformats as well as starting to explore ‘capital letter’ Semantic Web formats. Steve Ganz, LinkedIn’s Principal Web Developer, talks about how LI uses hReview, hResume, hEvent, hCard and XHTML Friends Network (aka XFN) to enable users to do more with their data than just read it on a web page. And obviously, apart from the mash-up possibilities, there are a growing number of SEO advantages to enabling the site in this way.

The article also talks tantalisingly about some of the initial work LI is doing with Semantic Web approaches like Friend of a Friend and other RDF vocabularies.

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May 15, 2008

I’m sure everyone has had this simple idea before: keeping all that contact information in sync irrespective of whether it’s in your computer address book, mail address book, your mobile, your social network site etc. Well, Soocial is in a Dutch start-up in private beta right now and is aimed at exactly that: supporting over 400 models of mobile phone as well as Gmail, Highrise, Mac address book… You can allow other applications to use your contacts without passing on Soocial specific details using OAuth — natch.

I’m also just loving the punning visual design that Soocial uses — whether it’s a Knightrider star and pop icon to symbolise hassle-free synchronisation, or Sean Connery’s pistol-toting, nappy-wearing rendition of Zed in in Zardoz to show that something went wrong. Wonderful.

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Giant Global Graph

May 12, 2008

I really enjoyed this post on Giant Global Graph. This is analogous to the World Wide Web. Timbl explains that we have gone through a number of revolutions

  • From thinking that cables and wires mattered to thinking that the computers connected to them were more important
  • From thinking that computers were important to thinking that documents residing on the computers were important
  • From thinking that documents were important to thinking that the things document discussed were important

This last stage is burgeoning right now: transforming useful graphs of information such as the social graph of who is friends with whom into an open format that can be used by any site: full data portability. In the medium term, this will bring higher quality traffic to sites whilst enabling users to worry less about (for instance) whether they’ve joined Plaxo, facebook, Gmail, digg, LinkedIn or Skype but to enable a new site to access their social graph easily.

Plaxo, Facebook and Google joined in the data portability project not so ago. More recently, news arrived that Yahoo! Search are starting to crawl for common RDF vocabularies and microformats is a massive step in the right direction. So far, many efforts to make the Semantic Web have been hard to kick-start. In a recent podcast, Peter Mika from Yahoo! Research uses the analogy of the chicken and the egg. Do you start pumping out data in semantic web formats or do you start creating apps that use the data to do something useful? Peter says: “we start building a chicken farm” by getting Yahoo! Search to crawl the web for the semantic data, baking that into more relevant and useful search results for users that direct better quality traffic to the host sites.

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Great visual introduction to DataPortability

May 12, 2008

DataPortability – Connect, Control, Share, Remix from Smashcut Media on Vimeo.

The above video gives a great visual intro to what the DataPortability project is all about.

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Powerset goes live

May 11, 2008

Well, it’s finally time. After months of private alpha and beta testing, Powerset is finally launching (as I write this, it’s still in beta — you should see a change in the next day). Tipped as natural language based search to beat Google, I’ve been testing the $12.5 million start-up for a while and I admit to being impressed. Through the ‘Powerlabs’ I’ve been checking out a number of different search apps that promise to translate real English into search results, instead of forcing everyone to work through Keywordese, the Pidgin English that everyone uses to access Google, Yahoo! or whatever search engine is your flavour of the month.

Currently the demos which work on Wikipedia and Freebase have had some fantastic reviews. As TechCrunch says

“When I tested the service I had something very similar to the ”Aha!“ feeling that ran through me the first time I ever used Google. In short, it is an evolutionary, and possibly revolutionary, step forward in search.”

I didn’t get this feeling. A lot of my searches worked but they did not come back with the single answer I was looking for. Also, remember that true Natural Language based search is the holy grail of search. Which is another way of saying it may be almost completely unobtainable. However, it remains a lot better than a lot of the Google, Ask or Yahoo! searches I do regularly. The power of the search itself in its capability to handle relatively complex queries with good grace. For instance, “Who killed JFK?” and “Who killed Princess Diana?” are both pretty easy but questions like “Will there be a recession?” or “Show buildings by Gaudi” or “How many dimensions does string theory postulate?” or “What are the ingredients of pastitsio?” are a bit trickier.

PowerSet has two huge hurdles to overcome. First, it is a classic AI ‘model world’ which only covers a small subset of what people really want to search (i.e. the web) and this has taken a long time to get right. Second, it still needs a good marketing and product approach — great technology doth not a killer app make.

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Yoskovitz: Be a Data Hog, Make More Money!

May 9, 2008

Ben Yoskovitz is known for his company Standout Jobs. In the article “Yoskovitz: Be a Data Hog, Make More Money!” he makes a good and simple case for collating lots of data, analysing it regularly and repeatedly asking Why? The approach reminded me a lot of my colleague Doug Brown, the executive in charge of operations in our Search Engine Marketing reseller division. Doug is constantly driving his team to build up data, analyse and test it, and then make interesting and useful predictions and conclusions.

There is a link here with highly iterative development. It comes down to generating and understanding feedback from a working system as quickly as possible and then being able to adjust your course as quickly as possible with the new information. Making the feedback small, incremental and falsifiable (as in test-driven development) is important. Each of these contributes to being able to translate the tests into next actionable steps.

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