|By Charles Silver||
|December 18, 2013 09:18 AM EST||
Whether you've bought into it yet or not, the Semantic Web (aka Web 3.0) is coming - and mega-companies are leading the way. Not just the Googles, Facebooks and Apples of the world, but also massive organizations with business models as diverse as Wal-Mart, The New York Times, Dow Jones and Ford. All of them, and many more, are heavily invested in semantic web technologies.
One reason: When the transition to the Semantic Web is complete, all data everywhere will be linked in the cloud as connected points on a massive global graph. Unlike data in silos, the linked data in graphs allows computers to read it, understand it, infer meaning and produce an answer that's exactly what the searcher is looking for, whether the searcher is a shopper, reporter, marketer, financial analyst, cancer researcher or even the CIA.
Semantic search doesn't just yield a far better Web experience. It tremendously increases knowledge, understanding, click-thrus, conversions, opportunities and intelligent decision making.
If you're the biggest retailer in the world - aka Wal-Mart - and have one of the biggest data piles on the planet plus audacious e-commerce goals, you figured this out a while ago and made getting onto the Semantic Web a huge priority. Not least because, in one observer's words, "The retail giant needs to keep getting smarter if it wants to compete with Amazon, the leader in online retail."
Here's how to do it STAT:
Step one: Jumpstart the process and buy a semantic technology company
Wal-Mart acquired Kosmix, a semantic company that connects people, places, topics, events and products, in April 2011, changing its name to @Wal-MartLabs. Estimated price: $300 million or so. (Digital trivia: The team that built Kosmix also built what was probably the first shopping search engine ever, which Amazon bought for $250 million in - ancient history alert - 1998.)
Step two: Build your own semantic search engine
Barely 15 months later, @Wal-MartLabs announced that it had built and deployed Polaris, its own semantic search engine, on Walmart.com, with speedy results: "It has already boosted conversions to sales by 10-15 percent." Why? It gets what you want. For example, if you search for a Kindle, which Wal-Mart doesn't sell (take that, Amazon), Polaris instantly understands what you're after and shows you a very competitively priced array of Kindle alternatives that it does sell - including plenty of Nooks and iPads.
Step three: Don't stop there
In 2013 alone, Wal-Mart bought Inkiru, Torbit, OneOps and Tasty Labs for improved semantic search, better mobile support and optimization of its Big Data capabilities, including fraud detection.
Step four: Reap the ROI rewards
While the company has spent millions (no one will say how many, but many), the payoff is in the billions. For the current fiscal year, Wal-Mart expects to have $9 billion in online sales, a nearly 50 percent increase from its estimated 2011 online sales of $6.31 billion.
Meanwhile, The New York Times, tight-money times or not, has forged ahead with its own semantic strategy: the imperative if daunting task of getting all of its articles and information in a semantic database called rNews. The Gray Lady not only is spending a tidy bundle on doing this but also on working with Schema.org to establish global standards for making news data semantic.
In fact, whole industries have been going on semantic shopping sprees, particularly financial services (the likes of Dow Jones, Bloomberg LP, Citigroup), pharmaceuticals (Merck, Pfizer, Eli Lilly, J&J) and car companies (Ford, Audi, Volkswagen). These and other mega-companies are buying and/or building their own internal semantic solutions as fast as they can find the right tech.
Like the Titans of Technology (Google, Microsoft, Facebook, Apple, et al), the Titans of Business know the Semantic Web is a must to harvest the limitless knowledge inside Big Data. In their world, Web 3.0 is already happening. Many are hunting hard for the urgently needed next big breakthrough in semantic technology: a high-performance, affordable graph platform that will explode the development of RDF applications, including site-specific search, and transform Web 3.0 from vision to reality.
Once the price and performance issues for semantic RDF applications are solved, the new opportunities are endless. The global impact on business, research and society will be far more disruptive than Web 1.0 ever was.
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