HERE Search uses a machine learning system to rank search results, as do most major location-based search engines. The system "learns" from real-world queries randomly sampled from search logs. Human annotators look at the results provided by the system and rate them by quality. These ratings are fed back into the system so that it can learn from its mistakes and constantly improve over time, adapting to changing query types, new application releases and data updates, and the growing geographic distribution of users.
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