Recent discussions reveal that Google's Navboost system is a straightforward database rather than a complex machine learning model, as clarified by Dr. Eric Lehman. Furthermore, most search signals utilized in Googleâs ranking algorithms, other than a couple based on large language models, are hand-crafted by engineers who analyze data to determine thresholds. This highlights a structured approach in refining search results, countering previous claims by Google that certain user engagement metrics, like pogosticking, do not play a role in rankings.
Navboost is not a machine-learning system. It's just a big table.
Almost every signal, aside from RankBrain and DeepRank, are hand-crafted and thus able to be analyzed and adjusted by engineers.
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