In addition to EGOL and Robert's insights, we also see Google behavior like this in a couple of other areas.
In search changes around News results when real-time feeds based appear in parallel with search query volume and page changes across the web we see news items gaining a boost. If a new brand is gaining similar traction on both sides of search (both press and searcher interest) it's not a small leap to think that Google will respond with providing users more results around that brand.
Another good parallel comes from the Google patent for "Using concepts as contexts for query term substitutions" ( https://www.google.com/patents/US9104750 ). Being a patent around context and similar terminology, its Claim #1 is broken down as First Term + Second Term + Third Term = something different than any one of those terms used alone. Their example further on in the patent is especially telling...
During state (I), the substitution engine 206 analyzes the aggregated query term substitution data, and determines whether one or more substitution rules may be generated from the analysis. For one example, the substitution engine 206 may determine from the query term substitution data 231 that the term “Crossword” is frequently a substitute term for the term “Puzzle” in the context of the concept “New York Times,” as indicated by a positive indication 237. In some implementations, the indication 237 may be a quantitative score assigned to the query term substitution data 231 in the query log 209, and the quantitative score can be analyzed by one or more criteria in the substitution engine's evaluation of a potential substitute term. For another example, the substitution engine 206 may determine from the query term substitution data 233 that the term “Subscription” is not frequently a substitute term for the term “Puzzle” in the context of the concept “New York Times,” as indicated by a negative indication 238. Here, the substitution engine 206 determines that the term “Crossword” is frequently a substitute term for the term “Puzzle” in the context of “New York Times”, and sends an indication 239 to the collection 210 of substitution rules to add the substitution rule “Puzzle→Crossword (New York Times :)” to the collection 210. For subsequent user queries that contain original query terms “New York Times Puzzles”, the substitution engine 206 may then apply the substitution rule “Puzzle→Crossword (New York Times :)” and communicate with the query reviser engine 205 to include the substitute term “Crossword” in the revised query.
While the example above goes into the similarities between the terms "Puzzle" and "Crossword" the same machine learning can recognize and attribute values to the brand itself, "New York Times".