GH issue, search score ranking

Author: HeidiSteen

articles/search/index-ranking-similarity.md

@@ -7,7 +7,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: how-to
-ms.date: 10/14/2022
+ms.date: 04/18/2023
 ---
 
 # Configure relevance scoring
@@ -18,10 +18,10 @@ Configuration changes are scoped to individual indexes, which means you can adju
 
 ## Default scoring algorithm
 
-Depending on the age of your search service, Azure Cognitive Search supports two [similarity scoring algorithms](index-similarity-and-scoring.md) for assigning relevance to results in a full text search query:
+Depending on the age of your search service, Azure Cognitive Search supports two [similarity scoring algorithms](index-similarity-and-scoring.md) for a full text search query:
 
-+ An *Okapi BM25* algorithm, used in all search services created after July 15, 2020
-+ A *classic similarity* algorithm, used by all search services created before July 15, 2020
++ Okapi BM25 algorithm (after July 15, 2020)
++ Classic similarity algorithm (before July 15, 2020)
 
 BM25 ranking is the default because it tends to produce search rankings that align better with user expectations. It includes [parameters](#set-bm25-parameters) for tuning results based on factors such as document size. For search services created after July 2020, BM25 is the only scoring algorithm. If you try to set "similarity" to ClassicSimilarity on a new service, an HTTP 400 error will be returned because that algorithm is not supported by the service.
 

articles/search/index-similarity-and-scoring.md

@@ -7,7 +7,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: conceptual
-ms.date: 10/14/2022
+ms.date: 04/18/2023
 ---
 
 # Relevance and scoring in Azure Cognitive Search
@@ -41,7 +41,12 @@ If you want to break the tie among repeating scores, you can add an **$orderby**
 
 ## Scoring algorithms in Search
 
-Azure Cognitive Search provides the `BM25Similarity` ranking algorithm. On older search services, you might be using `ClassicSimilarity`.
+Azure Cognitive Search provides the following scoring algorithms:
+
+| Algorithm | Usage | Range |
+|-----------|-------------|-------|
+| BM25Similarity | Built-in algorithm on all search services created after July 2020. You can tune relevance ranking, but on newer services, changing the algorithm isn't supported. | Unbounded range |
+|ClassicSimilarity | Used on older search services. You can [opt-in for BM25](index-ranking-similarity.md). | 0 < 1.00 |
 
 Both BM25 and Classic are TF-IDF-like retrieval functions that use the term frequency (TF) and the inverse document frequency (IDF) as variables to calculate relevance scores for each document-query pair, which is then used for ranking results. While conceptually similar to classic, BM25 is rooted in probabilistic information retrieval that produces more intuitive matches, as measured by user research. 
 

articles/search/search-pagination-page-layout.md

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: how-to
-ms.date: 11/02/2022
+ms.date: 04/18/2023
 ---
 
 # How to work with search results in Azure Cognitive Search
@@ -66,7 +66,7 @@ Count won't be affected by routine maintenance or other workloads on the search
 
 ## Paging results
 
-By default, the search engine returns up to the first 50 matches. The top 50 are determined by search score, assuming the query is full text search or semantic search. Otherwise, the top 50 are an arbitrary order for exact match queries (where "@searchScore=1.0").
+By default, the search engine returns up to the first 50 matches. The top 50 are determined by search score, assuming the query is full text search or semantic search. Otherwise, the top 50 are an arbitrary order for exact match queries (where uniform "@searchScore=1.0" indicates arbitrary ranking).
 
 To control the paging of all documents returned in a result set, add `$top` and `$skip` parameters to the query request. The following list explains the logic.
 
@@ -109,9 +109,11 @@ Sorting methodologies aren't designed to be used together. For example, if you'r
 
 ### Ordering by search score
 
-For full text search queries, results are automatically ranked by a search score, calculated based on term frequency and proximity in a document (derived from [TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf)), with higher scores going to documents having more or stronger matches on a search term.
+For full text search queries, results are automatically [ranked by a search score](index-similarity-and-scoring.md), calculated based on term frequency and proximity in a document (derived from [TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf)), with higher scores going to documents having more or stronger matches on a search term.
 
-The "@search.score" range is 0 up to (but not including) 1.00. A "@search.score" equal to 1.00 indicates an unscored or unranked result set, where the 1.0 score is uniform across all results. Unscored results occur when the query form is fuzzy search, wildcard or regex queries, or an empty search (`search=*`). If you need to impose a ranking structure over unscored results, an **`$orderby`** expression will help you achieve that objective.
+The "@search.score" range is either unbounded, or 0 up to (but not including) 1.00 on older services. 
+
+For either algorithm, a "@search.score" equal to 1.00 indicates an unscored or unranked result set, where the 1.0 score is uniform across all results. Unscored results occur when the query form is fuzzy search, wildcard or regex queries, or an empty search (`search=*`). If you need to impose a ranking structure over unscored results, an **`$orderby`** expression will help you achieve that objective.
 
 Search scores convey general sense of relevance, reflecting the strength of match relative to other documents in the same result set. But scores aren't always consistent from one query to the next, so as you work with queries, you might notice small discrepancies in how search documents are ordered. There are several explanations for why this might occur.
 

articles/search/search-query-odata-search-score-function.md

@@ -8,7 +8,7 @@ author: bevloh
 ms.author: beloh
 ms.service: cognitive-search
 ms.topic: reference
-ms.date: 09/16/2021
+ms.date: 04/18/2023
 translation.priority.mt:
   - "de-de"
   - "es-es"
@@ -25,6 +25,8 @@ translation.priority.mt:
 
 When you send a query to Azure Cognitive Search without the [**$orderby** parameter](search-query-odata-orderby.md), the results that come back will be sorted in descending order by relevance score. Even when you do use **$orderby**, the relevance score will be used to break ties by default. However, sometimes it is useful to use the relevance score as an initial sort criteria, and some other criteria as the tie-breaker. The `search.score` function allows you to do this.
 
+The relevance score is computed by the similarity ranking algorithm, and the range varies depending on which algorithm you use. For more information, see [Relevance and scoring in Azure Cognitive Search](index-similarity-and-scoring.md).
+
 ## Syntax
 
 The syntax for `search.score` in **$orderby** is `search.score()`. The function `search.score` does not take any parameters. It can be used with the `asc` or `desc` sort-order specifier, just like any other clause in the **$orderby** parameter. It can appear anywhere in the list of sort criteria.