But what Google has clearly started to do here is an extension of classic Information Retrieval (IR) techniques also applied in its search products. About time

But what Google has clearly started to do here is an extension of classic Information Retrieval (IR) techniques also applied in its search products. About time. Basic IR intro, skip this paragraph if you know the drill: Basic text search can be thought of as "looking for your search terms in relevant documents" (ala TF-IDF[1]). More sophisticated search layers on various other metrics. Google famously employed its Page Rank algorithm[2] as one such example. Modern search engines with enough traffic can also use click streams themselves as a search metric: for the given search terms, which link(s) were actually clicked on? Back on point: What users click on and where they go (if the data is available) and how many times they go (again, if the data is available) are usable metrics, physical equivalents of click-stream traffic. Likewise, information from other sources about relatedness of locations can also be integrated. Think "semantic fisheye views." E.g. you clicked on a pub, and Google knows about other pubs and bars in the area. Or perhaps you clicked on a Yoga studio, which causes different location relationships to be (de-)emphasized. Google at very least can draw on their classic search data as well as the more structured location and business data they've been building for some time. [1] https://en.wikipedia.org/wiki/Tf%E2%80%93idf https://en.wikipedia.org/wiki/Tf%E2%80%93idf [2] https://en.wikipedia.org/wiki/PageRank https://en.wikipedia.org/wiki/PageRank