Exploring The Google Knowledge Graph Search API
The Google Knowledge Graph Search API on a query for Google shows the following Entities and results in scores for them. I thought they were diverse enough to be interesting and worth sharing. A couple of the ones listed seem odd, such as the Indian Action movie. “Thuppakki” and the Town in Kansas, “Topeka.” (It seems like there is a song titled “Google Google” in the film Thuppakki, and in 2010 Topeka renamed itself “Google” to try to attract Google Fiber to the area.) We are told by Google that “Results with higher result scores are considered better matches.”
These are the Google Knowledge Graph Search API results on a search for Google:
Google “resultScore”: 292.863342 Google Chrome “resultScore”: 51.392109 X “resultScore”: 51.392109 Googleplex “resultScore”: 44.052853 Google China “resultScore”: 30.75222 Google Lively “resultScore”: 30.75222 DoubleClick “resultScore”: 29.141159 GV “resultScore”: 28.957876 Thuppakki “resultScore”: 28.693569 Google Store “resultScore”: 26.077885 “Google Japan” “resultScore”: 24.272602 DeepMind Technologies “resultScore”: 24.115602 Topeka “resultScore”: 23.718664 Rich Miner “resultScore”: 21.961121 Google Capital “resultScore”: 21.048887 Google Hacks “resultScore”: 21.003328 “Google Korea” “resultScore”: 20.818398 Barney Google and Snuffy Smith “resultScore”: 20.384176 Verily Life Sciences “resultScore”: 19.65727 Patrick Pichette “resultScore”: 19.614473
I’ve asked a couple of Google Webmaster evangelists if they could provide more information about how results scores are calculated, and I’m still waiting for answers from them.