Posts Tagged ‘Intelligence’
Top-Down: A New Approach to the Semantic Web
As things stand today, there is little reason for web site owners to do that. The tools that would leverage the annotated information do not exist and there has not been any clearly articulated business and consumer value. Which means that there is no incentive for the sites to invest money into being compatible with the semantic web of the future.
In this post, we will look at the solution that we call the top-down approach to the semantic web, because instead of requiring developers to change or augment the web, this approach leverages and builds on top of current web as-is.
Why Do We Need The Semantic Web?
The complexity of original vision of the semantic web and lack of clear consumer benefits makes the whole project unrealistic. The simple question: Why do we need computers to understand semantics? remains largely unanswered.
While some of us think that building AI is cool, the majority of people think that AI is a little bit silly, or perhaps even unsettling. And they are right. AI for the sake of AI does not make any sense. If we are talking about building intelligent machines, and if we need to spend money and energy annotating all the information in the world for them, then there needs to be a very clear benefit.
Stated the way it is, the semantic web becomes a vision in search of a reason. What if the problem was restated from the consumer point of view? Here is what we are really looking forward to with the semantic web:
- Spend less time searching
- Spend less time looking at things that do not matter
- Spend less time explaining what we want to computers
A consumer focus and clear benefit for businesses needs to be there in order for the semantic web vision to be embraced by the marketplace.
What If The Problem Is Not That Hard?
If all we are trying to do is to help people improve their online experiences, perhaps the full “understanding” of semantics by computers is not even necessary. The best online search tool today is Google, which is an algorithm based, essentially, on statistical frequency analysis and not semantics. Solutions that attempt to improve Google by focusing on generalized semantics have so far not been finding it easy to do so.
The truth is that the understanding of natural language by computers is a really hard problem. We have the language ingrained in our genes. We learn language as we grow up. We learn things iteratively. We have the chance to clarify things when we do not understand them. None of this is easily replicated with computers.
But what if it is not even necessary to build the first generation of semantic tools? What if instead of trying to teach computers natural language, we hard-wired into computers the concepts of everyday things like books, music, movies, restaurants, stocks and even people. Would that help us be more productive and find things faster?
Simple Semantics: Nouns And Verbs
When we think about a book we think about handful of things – title and author, maybe genre and the year it was published. Typically, though, we could care less about the publisher, edition and number of pages. Similarly, recipes provoke thoughts about cuisine and ingredients, while movies make us think about the plot, director, and stars.
When we think of people, we also think about a handful of things: birthday, where do they live, how we’re related to them, etc. The profiles found on popular social networks are great examples of simple semantics based around people:
Books, people, recipes, movies are all examples of nouns. The things that we do on the web around these nouns, such as looking up similar books, finding more people who work for the same company, getting more recipes from the same chef and looking up pictures of movie stars, are similar to verbs in everyday language. These are contextual actuals that are based on the understanding of the noun.
What if semantic applications hard-wired understanding and recognition of the nouns and then also hard-wired the verbs that make sense? We are actually well on our way doing just that. Vertical search engines like Spock, Retrevo, ZoomInfo, the page annotating technology from Clear Forrest, Dapper, and the Map+ extension for Firefox are just a few examples of top-down semantic web services.
The Top-Down Semantic Web Service
The essence of a top-down semantic web service is simple – leverage existing web information, apply specific, vertical semantic knowledge and then redeliver the results via a consumer-centric application. Consider the vertical search engine Spock, which scans the web for information about people. It knows how to recognize names in HTML pages and it also looks for common information about people that all people have – birthdays, locations, marital status, etc. In addition, Spock “understands” that people relate to each other. If you look up Bush, then Clinton will show up as a predecessor. If you look up Steve Jobs, then Bill Gates will come up as a rival.
In other words, Spock takes simple, everyday semantics about people and applies it to the information that already exists online. The result? A unique and useful vertical search engine for people. Further, note that Spock does not require the information to be re-annotated in RDF and OWL. Instead, the company builds adapters that use heuristics to get the data. The engine does not actually have full understanding of semantics about people, however. For example, it does not know that people like different kinds of ice cream, but it doesn’t need to. The point is that by focusing on a simple semantics, Spock is able to deliver a useful end-user service.
Another, much simpler, example is the Map+ add-on for Firefox. This application recognizes addresses and provides a map popup using Yahoo! Maps. It is the simplicity of this application that precisely conveys the power of simple semantics. The add-on “knows” what addresses look like. Sure, sometimes it makes mistakes, but most of the time it tags addresses in online documents properly. So it leverages existing information and then provides direct end user utility by meshing it up with Yahoo! Maps.
The Challenges Facing The Top-Down Approach
Despite being effective, the somewhat simplistic top-down approach has several problems. First, it is not really the semantic web as it is defined, instead its a group of semantic web services and applications that create utility by leveraging simple semantics. So the proponents of the classic approach would protest and they would be right. Another issue is that these services do not always get semantics right because of ambiguities. Because the recognition is algorithmic and not based on an underlying RDF representation, it is not perfect.
It seems to me that it is better to have simpler solutions that work 90% of the time than complex ones that never arrive. The key questions here are: How exactly are mistakes handled? And, is there a way for the user to correct the problem? The answers will be left up to the individual application. In life we are used to other people being unpredictable, but with computers, at least in theory, we expect things to work the same every time.
Yet another issue is that these simple solutions may not scale well. If the underlying unstructured data changes can the algorithms be changed quickly enough? This is always an issue with things that sit on top of other things without an API. Of course, if more web sites had APIs, as we have previously suggested, the top-down semantic web would be much easier and more certain.
While the original vision of the semantic web is grandiose and inspiring in practice it has been difficult to achieve because of the engineering, scientific and business challenges. The lack of specific and simple consumer focus makes it mostly an academic exercise. In the mean time, existing data is being leveraged by applying simple heuristics and making assumptions about particular verticals. What we have dubbed top-down semantic web applications have been appearing online and improving end user experiences by leveraging semantics to deliver real, tangible services.
Will the bottom-up semantic web ever happen? Possibly. But, at the moment the precise path to get there is not quite clear. In the mean time, we can all enjoy better online experience and get to where we need to go faster thanks to simple top-down semantic web services.
Dave McComb : What will it take to build the Semantic Technology industry?
Dave McComb, CEO of asemantics and co-chair of this year’s Semantic Technology Conference in San Jose / USA, does not believe in killer applications when it comes to capitalize semantic technologies. Read his comment on what it takes to build a Semantic Technology industry.
What will it take to build the Semantic Technology industry?
I get asked this question a lot. And I’d like to get your help in answering it please.
As co-chair of the Semantic Technology Conference program, I see lots of customer organizations experimenting and adopting semantic technologies – especially ontology-driven development projects and semantic search tools – and seemingly as many start-ups and new products emerging to address their requirements. It’s an exciting time to be in this space and I’m glad to have a part to play.
But back to the question of “what will it take?” I don’t think anyone has all the answers, though it seems there’s a growing consensus about how semantics will eventually take hold:
1. A Little Semantics Goes a Long Way
I think it was Jim Hendler who first used the expression, and I find myself in stark agreement. Much of the criticism of the semantic web vision focuses on the folly of trying to boil the ocean, yet many of the successful early adopters are getting nice results by taking small incremental steps. There’s a nice little exchange at Dave Beckett’s blog on this point.
2. Realistic Expectations
I guess this relates to my first point, but I remain concerned about the hype and expectations that are being set around the semantic web, and now the term Web 3.0. As much as anyone, I’d love to see semantics grow exponentially. But this market is going to be driven by customers, not vendors, and the corporate clients I see have hyped too many times so they’re taking a more cautious approach. I’m confident they’ll catch on eventually, but let’s not try to push them too far, too fast.
3. We Don’t Need a Killer App
Personally I think we need to look at semantic capabilities as an increasing component of the web and computing infrastructure, as opposed than trying to identify a killer app that’s going to kickstart a buying frenzy. If a killer app emerges then that’s great, but don’t hold your breath. There’s plenty of value to be gained in the meantime. More than anything, we need to demonstrate speedy, cheap ways to get started with semantics. This will be far more useful in the long run.
4. We Need to Get Business Mindshare
It’s so obvious that I’m almost embarrassed to say it, but the main point is that we need to improve how we’re currently demonstrating the business value of semantic technology. I see a few key ways we can improve, starting with a greater willingness to talk about the projects already taking place. Secondly, I think we can leverage existing technology trends – especially SOA and mashups – to show how semantic technology can add value to these efforts. Third, and I risk offending a few people with this, but in the short term we should be emphasizing cost savings and reduced time to deployment over and above the extra intelligence and functionality that semantics can provide. Especially for corporate customers. Semantic SOA can save hugely over conventional approaches in data integration and interface projects, and this is where most businesses are really feeling the pain right now.
OK, so this is a short and incomplete list of ideas, and I’ll admit that part of my motivation is just to get the conversation started. But I hope you’ll join in. There are two places where you can start:
This year’s SemTech conference in particular will have numerous discussions around the theme of how to grow the semantic technology industry, including Mills Davis’ Semantic Wave 2007 tutorial, and the Keynote panel on Building the Semantic Technology Industry: A Conversation with Entrepreneurs and Investors.
I hope to see you in one place or the other, and to get your input to the conversation.
Nova Spivack : “Web 3.0 will combine the Semantic Web with social media, enabling a new generation of richer, more shareable, mashable content.”
Nova Spivack, CEO of Radar Networks and inventor of the term Web 3.0, gives a micro-interview to Tassilo Pellegrini on the logic of versioning the internet, popularizing the Semantic Web and the secrets of the Radar Networks Laboratories.
People have hardly got used to the concept of Web 2.0 then suddenly you came up with a term called Web 3.0 and shortly Web 4.0. What is the logic behind versioning the Internet?
My proposal is that we use these terms to index decades of the Web. Web 1.0 was 1990 – 2000 and the focus was mainly about the backend of the Web (HTML, http). Web 2.0 is 2000 – 2010 and has been mainly about the front-end of the Web (usability, AJAX, tagging, etc.). Web 3.0 will be 2010 – 2020 and will be about the backend again (RDF, Sparql and the Semantic Web) – it will upgrade the content of the Web. Web 4.0 will be from 2020 – 2030 and will be about the front-end again – a smarter, more proactive and productive Web in which apps will be able to reason and help users intelligently.
To me Web 3.0 seems like a mixture of social software and Semantic Web combining the principles of socially generated content and semantic interoperability. Could you agree on this? What is your explanation?
Yes I agree that Web 3.0 will combine the Semantic Web with social media, enabling a new generation of richer, more shareable, mashable content.
So where does the Semantic Web come in? Could it be that the W3C’s concept of a Semantic Web (despite its greatness) is too purist, too technology centred, which finally makes it difficult when it comes to outreach?
I think that the W3C’s original vision of the Semantic Web focused mainly on the value to software. But the Semantic Web will also be valuable to end-users, publishers, advertisers, buyers & sellers. The end-user benefits were not emphasized or even illustrated very much in the original vision. But that makes sense – the W3C is mainly focused on open standards for software. Today those of us who are promoting Web 3.0 are really focusing more on the benefits of semantics to end-users – regular non-technical end-users. That is ultimately the most important story to tell in order to bring about mainstream adoption.
Your company Radar Networks is still operating in stealth mode but a lot of people are really curious what it will reveal later this year. So what is behind the curtains? How will you apply the Web 3.0 principles in your products?
Well we’re in stealth as you point out so I can’t say so much yet. But we’re trying to bring the Semantic Web to ordinary non-technical end-users. Our application is a hosted Web-based service that will enable anyone to build and share their own Semantic website.
About Nova Spivack
Mr. Spivack has a BA in Philosophy, with a focus on cognitive science and artificial intelligence, from Oberlin College and a CSS degree from the International Space University a NASA-funded graduate professional business school for the space industry. In 1999 Mr. Spivack’s interest in space gave him the opportunity to help pioneer the early days of space tourism when he flew to the edge of space with Space Adventures and did micro-gravity parabolic flight training with the Russian air force.
Mr. Spivack’s weblog, Minding the Planet, focuses on Radar Networks and emerging technologies and can be read at http://www.mindingtheplanet.net.
A full version of his biography can be found here.
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