Google takes pride in tweaking algorithms to “serve better results,” yet somehow, these results get crappier by the minute. In a recent blog post introducing the Knowledge Graph, “which will help you discover new information quickly and easily” (according to Google), Googler Amit Singhal explains how things are supposedly improved, and how search evolves for the better.
“This is a critical first step towards building the next generation of search, which taps into the collective intelligence of the web and understands the world a bit more like people do,” he writes.
He takes [taj mahal] as a query, to illustrate how Knowledge Graph works, and explains how Google now understands the various meanings of this query: one of the world’s most beautiful monuments, the Taj Mahal musician, the famous casino in Atlantic City, NJ, the nearest Indian restaurant, and so on. The screenshot below reveals how these results are clustered based on their different meanings on the first results page in search:
Although in theory Google’s Knowledge Graph isn’t just rooted in public sources such as Freebase, Wikipedia and the CIA World Factbook, the first two links are served by Wikipedia. In fairness, the official sites of Taj Mahal in Agra should come first, followed by official sites of The Trump Taj Mahal casino, then Taj Mahal the musician. Wikipedia, as an unofficial source of information, should fall down a few places, despite its popularity. This is not necessarily a matter of SEO, but a matter of truly serving the most relevant (and reliable) results for the user. The Taj Mahal in Agra is naturally first because it inspired every other Taj Mahal branded entity in the world.
The Knowledge Graph may be a great step forward, but it’s not enough. In fact, the results appear more confusing than ever. The example query involving Marie Curie shows clearly that Google’s, Pandas, Penguins and all other animals that will be released to “tweak” rankings, have serious limitations. The official site of the Institut Curie is nowhere in sight, and results from the Wikipedia still reign supreme.
The only true positive about the Knowledge Graph is the way it connects information, allowing you to “go deeper and broader,” seeing what relevant data other people are searching for, finding related topics, and so on. The promotional Knowledge Graph video below gives you an idea of Google’s intention of shifting from an “information engine” to a “knowledge engine.” The approach is to analyze user behaviors, considering what people search for a “collective intelligence.” The collective however, may not be the most relevant result – when people search for something, they usually do so because they need to gather reliable information, from accredited sources. Can Google eliminate the guessing game with its Knowledge Graph? Not as long as Wikipedia still holds the first position.
