1 / 5
Artificially raising the score of certain documents so they rank higher is called ___.
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Boosting increases the weight of fields or documents (e.g. recent or in-stock items) to lift them in the results.
2 / 5
Returning more of the relevant documents, even at the cost of some irrelevant ones, favours ___.
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Recall measures how many relevant results you retrieved; emphasising it casts a wider net but may add noise.
3 / 5
Ensuring most of the returned results are actually relevant favours ___.
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Precision measures how many returned results are relevant; tuning trades it off against recall depending on the use case.
4 / 5
A curated set of queries with known good results, used to measure tuning impact, is a ___ set.
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A golden (judgment) set lets you score relevance changes objectively, so a tuning tweak can be proven to help or hurt.
5 / 5
Which sentence explains a ranking change to a stakeholder clearly?
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Tying the change to a business-meaningful outcome (available products first) communicates impact better than internal parameter names.