Search with Automatic reranking:

Disabling reranking can make the results faster but may degrade results:

Use a smaller SemanticRanking model for some improvement in results:

Specify a custom reranking method as a function of the items:

Specify the reranker as a function of the items and the query:

Reranking defaults to a minimum of 10 candidate items retrieved from the database, then returns the requested number of MaxItems:

Disabling reranking will give the first result from the initial search:

Reduce the minimum number of candidate items provided to the reranker:

The number of candidates is calculated by taking the larger of "MinItems" and the product of the "MaxItemMultiplier" method option and the specified number of MaxItems:

Create an index with tags corresponding to the frequency of words in the text:

Default sorting gives close matches, but the first match may be obscure or only mentioned a few times in the text:

Rerank based on the most prevalent words:

Create an index:

Use a custom question when reranking to further refine the results:

Create an index:

Specify the size of the model to be used:

Using a larger SemanticRanking model can give better results at the cost of a longer evaluation time: