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Popularity boosting

As explained in AI-Powered Search

Popularity boosting increases the ranking score of documents according to a measure of their popularity.

Popularity boosting increases a document’s relevance score when its popularity signal is higher, allowing ranking to use more than text similarity. section 3.2.2

Treat popularity as a configurable scoring function alongside the default BM25 keyword calculation. A ranking expression can scale popularity and combine it with keyword, geographic, or date-based functions. section 3.2.2

Combining popularity with other signals

A function query can scale the keyword score, geographic distance, document date, and popularity together; a basketball query is shown with popularity scaled from 0 to 25. section 3.2.2

Solr request syntax:
 {"query": "{!func}scale(query($keywords),0,25)
     {!func}recip(geodist($lat_long_field,$user_latitude,
     $user_longitude),1,25,1)
     {!func}recip(ms(NOW/HOUR,modify_date),3.16e-11,25,1)
     {!func}scale(popularity,0,25)",
  "params": {"keywords": "basketball",
             "lat_long_field": "location",
             "user_latitude": 33.748,
             "user_longitude" -84.391}}

Inspect a concrete function-query listing that combines keyword relevance with geographic, date, and popularity functions. section 3.2.2

How AI-Powered Search covers it

How deep it goes
Shows configurable scoring functions and a combined function-query implementation without detailing popularity measurement.
Examples
Uses a basketball query and a function expression that scales popularity alongside keyword, geographic, and date signals.
What it assumes
Assumes familiarity with keyword similarity and introduces scoring functions as configurable parts of a query.
What you can do after
Apply popularity boosting by combining a scaled popularity function with keyword, geographic, and date-based ranking functions.
How it connects
Connects BM25 similarity with geospatial boosting, date boosting, and configurable query functions.

This explainer was generated by Manning's knowledge graph from the text of AI-Powered Search. The section links point to the parts of the book it draws on.