The idea of "semantic web" was first mentioned in an article featured in Scientific America over 5 years ago and was authored by web co-creator Tim Berners-Lee, Professor Jim Hendler and Professor Ora Lassila of Nokia. The idea behind the "semantic web" was to begin to make sense of data on the World Wide Web, which would inevitably impact on what is today known as search.
Almost all of the information on web pages is created by humans, and as we are all aware and take for granted our computers are great for viewing this information. But what if our computers could be shown how to extract meaning from the words and numbers within this information? "Increased intelligence", "next generation" and "bringing meaning to the web" were the hot topics of attendees at this years World Wide Web conference.
This concept may seem like the trailer a sci-fi blockbuster but, according to Professor Wendy Hall, head of the research team at the University of Southampton who are looking into the semantic web, it can be summed up as "creating a web that can be interpreted by machines".
So what does this mean? Professor Hall carries on to say that semantic searching "allows you to ask much more complex questions" when searching for information.
The semantic web could have a great impact on those industries where users provide set criteria for a search and expect a number of relevant results in return: for example, a couple searching for a new home would search for 'property for sale' and 'Edinburgh'. This search would return relevant results but the couple would have to work their way through the results finding a property that fits into their more selective criteria, near a particular school or shopping facilities for example.
The concept of semantic searching would prevent wasting time on refining these results, with users asking more specific questions and getting equivalent results. The data on the semantic web regarding properties would be available but would also be 'tagged' with descriptions telling computers what they are looking at.
On the semantic web the our couple could ask for information about properties in Edinburgh, costing £250,00 with three bedrooms, near a public school with good local shopping facilities and including, say, a supermarket. The semantic search engine would cross-reference all the information available about properties in Edinburgh with the request and produce results to match this query.
This is a great step, but Professor Hall continues to explain that this is only the tip of the iceberg. When discussing the subject of holiday search she explains, "Once you have all of that data on the web in a form that a machine can understand, then you can start having services like a personal agent that picks a holiday for you or even negotiates the price on your behalf."
These examples may apply to the domestic life of search, but developments over the last five years have had big business pay attention to the semantic web with financial markets, pharmaceutical companies and other data-heavy industries starting to get their data in order to cope with the introduction of the semantic web. The limits of this concept are difficult to imagine with the academic world highlighting that by comparing retail patterns from medical products, epidemiologists can pick up on disease patterns and even predict where a flu epidemic may have broken out - right down to the town or even street location.
With a test version of a semantic search engine called "Swoogle" at the University of Maryland the reality of this concept is speedily drawing closer, even though a definite definition of the semantic search may be mildly elusive, one thing that can be agreed on is that this development will have a great impact on search as we know it.
