For too long search design has been dictated either by the search engine technology i.e. “Keywords” or by the agregators (Google/Yahoo/MSN) ranking algorithms. Both have their benefits but neither necessarily serves the user the best.
Keywords work perfectly if you are searching for a product. If I want to know about the Treo 750W then typing that into any reviews site or search engine I’ll get very specific results. However if I wanted to find out about Smartphones, then things start to get messy. Firstly the term Smartphone means different things to different people. Secondly most product reviews probably won’t even mention the word “Smartphone” in them anyway. So keyword searching on a topic is a very hit and miss affair.
Using the main search engine sites, the problems are different but equally vexing for the user. At the mercy of the algorithm, users are now provided with content that has been deemed by some invisible mechanism important.
Google changed the landscape here by working out that what the users thought was important (i.e. Number of links to that content) was actually more relevant than the most recent content with that keyword. Of course, it’s not as simple as that and the big three spend millions of dollars tweaking and tuning their “special formula” with as much secrecy and security as Coca Cola.
Natural language search engines have been around for a long time but the problem has always been that it takes around 100 times more computing power to index and search in this way compared with conventional keyword search. Now, with processing power becoming cheaper and cheaper, we are starting to see investment ramp up in these technologies. Cited in this article, there were 47 search start-ups in 2005 raising a combined $260M.
And here on ZDNet, we are starting to experiment with this technology too. Our new search engine has the ability to automatically create relevant tags and topics related to the search term. It’s still early days for this type of technology but we believe that this type of search is the only one that considers the user first. Up to 75% of search terms are a single word and our most popular search term is often “Microsoft”.
Given the size and scope of Microsoft’s market, this would lead you to believe that the user doesn’t know how to search for what they are really looking for. And the truth is, most users are working blindfold when it comes to understanding conventional search syntax so they go in one direction until they bump into something, re-adjust and try again.
By creating tag clouds of the most relevant tags and terms, we are narrowing down the search for the user and helping them towards what they were really looking for. Go on, give it a try, take off your blindfold, click here and check out the related tags box.
