Archive for the 'semantic web' Category

Here’s a secret: the semantic web is the boring bit

Marshall Kirkpatrick caused a wave today, when he gave a brutally honest assessment of one of the most talked up semantic web applications, Twine. It was as per usual, an excellent analysis by Marshall and I don’t think he needs to hide behind his words as they are fair. However, what I think is crucial is now that the semantic web is gaining traction into the mainstream from a academic thesis to real world web applications, is we do a little bit of stakeholder management.

Ready? The semantic web is as boring as bat shit.

Essentially, the semantic web is about structuring content in a way so that computers can interpret the information. It’s a bit like linking every word on the web, to a dictionary entry so that computers understand the language that humans use.

But seriously, how is that exciting? People don’t get the semantic web, because it’s the fundamentals – and thats boring! Take for example RDF, the semantic web building block, and which is about structuring data into subject, predicate and object. This is straight from primary school grammar lessons, where we learn about the fundamentals of the English language (no coincidence I just linked to an grammar guide, not the RDF guide). And if you have heard of subject, predicate and object before in the context of the semantic web, you probably didn’t even realise it’s how the entire English language is based. It’s because you probably did learn it, and forgot – it’s boring as bat shit. But damn, without them, we wouldn’t be communicating right now to each other.

The point I want to make, is that the building blocks are not where the excitement: the excitement, is what you can do once we have those building blocks. In English, we have poetry, literature, and just language in general where we communicate as human beings. Once we get the basics down of information, we are laying the foundation of a whole new world of computational possibilities. Marshall is spot on in saying “…semantics may be best suited to the back end…” because the excitement is what they enable, not the actual semantics itself which is going to take a long time to build up.

Imagine, the sum of human knowledge accessible by a computer to query? Semantic web applications are boring and you won’t ever get them – but what they enable, is a whole new world of potential which once we can flick the switch, will mean a world we will barely recognise from today’s standpoint.

Don’t get the Semantic Web? You will after this

Prior to 2006, I had sort of heard of the Semantic Web. To be honest, I didn’t know much – it was just another buzzword. I’ve been hearing about Microformats for years, and cool but useless initiatives like XFN. However to me it was simply just another web thing being thrown around.

Then in August 2006, I came across Adrian Holovaty’s article where he argues journalism needs to move from a story-centric world to a data-centric world. And that’s when it dawned on me: the Semantic web is some serious business.

I have since done a lot of reading, listening, and thinking. I don’t profess to be a Semantic Web expert – but I know more than the average person as I have (painfully) put myself through videos and audios of academic types who confuse the crap out of me. I’ve also read through a myriad of academic papers from the W3C, which are like the times when you read a novel and keep re-reading the same page and still can’t remember what you just read.

Hell – I still don’t get things. But I get the vision, so that’s what I am going to share with you now. Hopefully, my understanding will benefit the clueless and the skeptical alike, because it’s a powerful vision which is entirely possible

1) The current web is great for humans; useless for machines
When you search for ambiguous terms, at best, search engines can algorithmically predict some sort of answer that partially answers your query. Sometimes not. But the complexity of language, is not something engineers can engineer to deal with. After all, without ambiguity of natural languages, the existence of poetry is impossible.


What did you think when you read that? As in: “I’ve had it – fine!” which is like another way of saying ok or agreeing with something. Perhaps you thought about that parking ticket I just got – illegal parking gets you fined. Maybe you thought I am applauding myself by saying that was one fine piece of wordcraftship I just wrote, or said in another context, like a fine wine.

Language is ambiguous, and depending on the context with other words, we can determine what the meaning of the word is. Search start-up company Powerset, which is hoping to kill Google and rule the world, is employing exactly this technique to improve search: intelligent processing of words depending on context. So by me putting in “it’s a fine”, it understands the context that it’s a parking ticket, because you wouldn’t say “it’s a” in front of ‘fine’ when you use it to agree with something (the ‘ok’ meaning above).

But let’s use another example: “Hilton Paris” in Google – the worlds most ‘advanced’ search engine. Obviously, as a human reading that sentence, you understand because of the context of those words I would like to find information about the Hilton in Paris. Well maybe.

Let’s see what Google comes up with: Of the ten search results (as of when I wrote this blog posting), one was a news item on the celebrity; six were on the celebrity describing her in some shape or form, and three results were on the actual Hotel. Google, at 30/70 – is a little unsure.

Why is Paris Hilton, that blonde haired thingy of a celebrity, coming up in the search results?

Technologies like Powerset apparently produce a better result because it understands the order of the words and context of the search query. But the problem with these searches, isn’t the interpretation of what the searcher wants – but also the ability to understand the actual search results. Powerset can only interpret so much of the gazilions of words out there. There is the whole problem of the source data, no just the query. Don’t get what I mean? Keep reading. But for now, learn this lesson

Computers have no idea about the data they are reading. In fact, Google pumping out those search results is based on people linking. Google is a machine, and reads 1s and 0s – machine language. It doesn’t get human language

2) The Semantic web is about making what human’s read, machine readable
Tim Berner’s Lee, the guy that invented the World Wide Web and the visionary behind the Semantic Web, prefers to call it the ‘data web’. The current web is a web of documents – by adding this extra data to content – machines will be able to understand it. Metadata, is data about data.

A practical outcome of having a semantic web, is that Google would know that when it pulls up a web page regardless of the context of the words – it will understand what the content is. Think of every word on the web, being linked to a master dictionary.

The benefit of the semantic web is not for humans – at least immediately. The Semantic Web is actually pretty boring with what it does – what is exciting, is what it will enable. Keep reading.

3) The Semantic web is for machines to interpret, not people
A lot of the skeptics of the semantic web, usually don’t see the value of it. Who cares about adding all this extra meta data? I mean heck – Google still was able to get the website I needed – the Hilton in Paris. Sure, the other 60% of the results on that page were irrelevant, but I’m happy.

I once came across a Google employee and he asked “what’s the point of a semantic web; don’t we already enough metadata?” To some extent, he’s right – there are some websites out there that have metadata. But the point of the semantic web is so that machines once they read the information, can start thinking like how a human would and connecting it to other information. There needs to be across the board metadata.

For example, my friend Michael was recently looking to buy a car. A painful process, because there are so many variables. So many different models, different makes, different dealers, different packages. We have websites, with cars for sale neatly categorised into profile pages saying what model it is, what colour it is, and how much. (Which may I add, are hosted on multiple car sites with different types of profiles). A human painfully reads through these profiles, and computes as fast as a human can. But a machine can’t read these profiles.

Instead of wasting his (and my) weekends driving around Sydney to find his car, a machine could find it for him. So, Mike would enter his profile in – what he requires in a car, what his credit limit is, what his prior history with cars are – everything that would affect his judgement of a car. And then, the computer can query every online website with cars to match the criteria. Because the computer can interpret these websites across the board, it can evaluate and it can go back to Michael and say “this is the car for you, at this dealer – click yes to buy”.

The semantic web is about giving computers the information to be able to interpret data, so that it can do what they do really well – compute.

4) A worldwide database
What essentially Berner’s Lee envisions, is turning the entire world wide web into a database that can be queried. Currently, the web looks like Microsoft Word – one swab of text. However, if that swab of text was neatly categorised in an Excel spreadsheet, you could manipulate that data and do what you please – create reports, reorder them, filter, and do whatever until your heart is content.

At university, I was forced to do an Information Systems subject which was essentially about the theory of databases. Damn painful. I learned only two things from that course. The first thing was that my lecturer, tutor, and classmates spoke less intelligible English than a caterpillar. But the second thing was that I learned what information is and how it differs from data. I am now going to share with you that lesson, and save you three months of your life.

You see, data is meaningless. For example, 23 degrees is data. On its own, it’s useless. Another piece of data in Sydney. Again, Рuseless. I mean, you can think all sorts of things when you think of Sydney, but it doesn’t have any meaning.

Now put together 23 degrees and Sydney, and you have just created information. Information is about creating relationships between data. By creating a relationship, an association, between these two different pieces of data – you can determine it’s going to be a warm day in Sydney. And that is what information is: Relationship building; connecting the dots; linking the islands of data together to generate something meaningful.

The semantic web is about allowing computers to be able to query the sum of human knowledge like one big database to generate information

Concluding thoughts
You are probably now starting to freak out and think “Terminator” images with computers suddenly erupting form under your computer desk, and smashing you against the wall as a battle between humans and computers begins. But I don’t see it like that.

I think about the thousands of hours humans spend trying to compute things. I think of the cancer research, whereby all this experimentation occurring in labs, is trying to connect new pieces of data with old data to create new information. I think about computers being about to query the entire taxation legislation to make sure I don’t pay any tax, because it knows how it all fits together (having studied tax, I can assure you – it takes a lifetime to only understand a portion of tax law). In short, I understand the vision of the Semantic web as a way of linking things together, to enable computers to compute – so that I can sit on my hammock drinking my beer, as I can delegate the duties of my life to the machines.

All the semantic web is trying to do, is making sure everything is structured in a consistent manner, with a consistent dictionary behind the content, so that a machine can draw connections. As Berner’s Lee said on one of the videos I saw: “it’s all about creating links”.

The process to a Semantic Web is boring. But once we have those links, we can then start talking about those hammocks. And that’s when the power of the internet – the global network – will really take off.

On the future of search

Robert Scoble has put together a video presentation on how Techmeme, Facebook and Mahalo will kill Google in four years time. His basic premise is that SEO’s who game Google’s algorithm are as bad as spam (and there are some pissed SEO experts waking up today!). People like the ideas he introduces about social filtering, but on the whole – people are a bit more skeptical on his world domination theory.

There are a few good posts like Muhammad‘s on why the combo won’t prevail, but on the whole, I think everyone is missing the real issue: the whole concept of relevant results.

Relevance is personal

When I search, I am looking for answers. Scoble uses the example of searching for HDTV and makes note of the top manufacturers as something he would expect at the top of the results. For him – that’s probably what he wants to see – but for me, I want to be reading about the technology behind it. What I am trying to illustrate here is that relevance is personal.

The argument for social filtering, is that it makes it more relevant. For example, by having a bunch of my friends associated with me on my Facebook account, an inference engine can determine that if my friend called A is also friends with person B, who is friends with person C – than something I like must also be something that person C likes. When it comes to search results, that sort of social/collaborative filtering doesn’t work because relevance is complicated. The only value a social network can provide is if the content is spam or not – a yes or no type of answer – which is assuming if someone in my network has come across this content. Just because my social network can (potentially) help filter out spam, doesn’t make the search results higher quality. It just means less spam results. There is plenty of content that may be on-topic but may as well be classed as spam.

Google’s algorithm essentially works on the popularity of links, which is how it determines relevance. People can game this algorithm, because someone can make a website popular to manipulate rankings through linking from fake sites and other optimisations. But Google’s pagerank algorithm is assuming that relevant results are, at their core, purely about popularity. The innovation the Google guys brought to the world of search is something to be applauded for, but the extreme lack of innovation in this area since just shows how hard it is to come up with new ways of making something relevant. Popularity is a smart way of determining relevance (because most people would like it) – but since that can be gamed, it no longer is.

The semantic web

I still don’t quite understand why people don’t realise the potential for the semantic web, something I go on about over and over again (maybe not on this blog – maybe it’s time I did). But if it is something that is going to change search, it will be that – because the semantic web will structure data – moving away from the document approach that webpages represent and more towards the data approach that resembles a database table. It may not be able to make results more relevant to your personal interests, but it will better understand the sources of data that make up the search results, and can match it up to whatever constructs you present it.

Like Google’s page rank, the semantic web will require human’s to structure data, which a machine will then make inferences – similar to how Pagerank makes inferences based on what links people make. However Scoble’s claim that humans can overtake a machine is silly – yes humans have a much higher intellect and are better at filtering, but they in no way can match the speed and power of a machine. Once the semantic web gets into full gear a few years from now, humans will have trained the machine to think – and it can then do the filtering for us.

Human intelligence will be crucial for the future of search – but not in the way Mahalo does it which is like manually categorising pieces of paper into a file cabinet – which is not sustainable. A bit like how when the painters of the Sydney harbour bridge finish painting it, they have to start all over again because the other side is already starting to rust again. Once we can train a machine that for example, a dog is an animal, that has four legs and makes a sound like “woof” – the machine can then act on our behalf, like a trained animal, and go fetch what we want; how those paper documents are stored will now be irrelevant and the machine can do the sorting for us.

The Google killer of the future will be the people that can convert the knowledge on the world wide web into information readeable by computers, to create this (weak) form of artificial intelligence. Now that’s where it gets interesting.

Google: the ultimate ontology

A big issue with the semantic web is ontologies – the use of consistent definitions to concepts. For those that don’t understand what I’m talking about – essentially, the next evolution of the web is about making content readable by not just humans but also machines. However for a machine to understand something it reads, it needs consistent definitions. Human’s for example, are intelligent – they understand that the word “friend” is also related to the word “acquaintance”, but a computer would treat them to mean two different things. Or do they?

Just casually looking at some of my web analytics, I noticed some people landed on my site by doing a google search for how many acquaintances do people have, which took them to a popular posting of mine about how many friends people have on facebook. I’ve had a lot of visitors because of this posting, and its been an interesting case study for me on how search engines work. However today was something different from other times: I found the word acquaintance weird. I know I didn’t use that word in my posting – and when I went to the Google cache I realised something interesting: because someone linked to me using that word, the search engine replaced the word ‘friend’ with ‘acquaintances’.


Google’s linking mechanism is one powerful ontology generator.