checkpoint

Author: HeidiSteen

articles/search/index-add-scoring-profiles.md

@@ -10,22 +10,22 @@ ms.service: cognitive-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 11/06/2023
+ms.date: 09/17/2024
 ---
 
 # Add scoring profiles to boost search scores
 
-In this article, you'll learn how to define a scoring profile. A scoring profile is critera for boosting a search score based on parameters that you provide. For example, you might want matches found in a "tags" field to be more relevant than the same match found in "descriptions". Criteria can be a weighted field (such as the "tags" example) or a function. 
+In this article, learn how to specify and assign a scoring profile. A scoring profile is criteria for boosting a search score based on parameters that you provide. For example, you might want matches found in a "tags" field to be more relevant than the same match found in "descriptions". Criteria can be a weighted field (such as the "tags" example) or a function. 
 
-Scoring profiles are defined in a search index and invoked on non-vector fields in query requests. You can create multiple profiles and then modify query logic to choose which one is used.
+Scoring profiles are defined in a search index and invoked on nonvector fields in query requests. You can create multiple profiles and then modify query logic to choose which one is used.
 
 > [!NOTE]
 > Unfamiliar with relevance concepts? The following [video segment on YouTube](https://www.youtube.com/embed/Y_X6USgvB1g?version=3&start=463&end=970) fast-forwards to how scoring profiles work in Azure AI Search. You can also visit [Relevance and scoring in Azure AI Search](index-similarity-and-scoring.md) for more background.
 >
 
 ## Scoring profile definition
 
-A scoring profile is named object defined in an index schema. A profile can be composed of weighted fields, functions, and parameters.
+A scoring profile is named object defined in an index schema. A scoring profile can be composed of weighted fields, functions, and parameters.
 
 The following definition shows a simple profile named "geo". This example boosts results that have the search term in the hotelName field. It also uses the `distance` function to favor results that are within 10 kilometers of the current location. If someone searches on the term 'inn', and 'inn' happens to be part of the hotel name, documents that include hotels with 'inn' within a 10 KM radius of the current location will appear higher in the search results.  
 
@@ -209,15 +209,15 @@ Use functions when simple relative weights are insufficient or don't apply, as i
 
 |Attribute|Description|  
 |---------------|-----------------|  
-| name | Required. This is the name of the scoring profile. It follows the same naming conventions of a field. It must start with a letter, can't contain dots, colons or @ symbols, and can't start with the phrase azureSearch (case-sensitive).|  
+| name | Required. Name of the scoring profile, folloiwng the same [naming conventions](/rest/api/searchservice/naming-rules) as field name. It must start with a letter, can't contain dots, colons, or @ symbols, and can't start with the phrase azureSearch (case-sensitive).|  
 | text | Contains the weights property.|  
-| weights | Optional. Name-value pairs that specify a searchable field and a positive integer or floating-point number by which to boost a field's score. The positive integer or number becomes a multiplier for the original field score generated by the ranking algorithm. For example, if a field score is 2 and the weight value is 3, the boosted score for the field becomes 6. Individual field scores are then aggregated to create a document field score, which is then used to rank the document in the result set. |  
-| functions | Optional. A scoring function can only be applied to fields that are filterable.|  
+| weights | Optional. Name-value pairs that specify a `searchable` field and a positive integer or floating-point number by which to boost a field's score. The positive integer or number becomes a multiplier for the original field score generated by the ranking algorithm. For example, if a field score is 2 and the weight value is 3, the boosted score for the field becomes 6. Individual field scores are then aggregated to create a document field score, which is then used to rank the document in the result set. |  
+| functions | Optional. A scoring function is applied to fields that are `filterable`.|  
 | functions > type | Required for scoring functions. Indicates the type of function to use. Valid values include magnitude, freshness, distance, and tag. You can include more than one function in each scoring profile. The function name must be lower case.|  
 | functions > boost | Required for scoring functions. A positive number used as multiplier for raw score. It can't be equal to 1.|  
-| functions > fieldname | Required for scoring functions. A scoring function can only be applied to fields that are part of the field collection of the index, and that are filterable. In addition, each function type introduces additional restrictions (freshness is used with datetime fields, magnitude with integer or double fields, and distance with location fields). You can only specify a single field per function definition. For example, to use magnitude twice in the same profile, you would need to include two definitions magnitude, one for each field.|  
+| functions > fieldname | Required for scoring functions. A scoring function is applied to fields that are `filterable`. Individual functions come with extra restrictions. For example, freshness is used with datetime fields, magnitude is used with integer or double fields, and distance is used with location fields. You can only specify a single field per function definition. For example, to use magnitude twice in the same profile, you would provide two definitions magnitude, one for each field.|  
 | functions > interpolation | Required for scoring functions. Defines the slope for which the score boosting increases from the start of the range to the end of the range. Valid values include Linear (default), Constant, Quadratic, and Logarithmic. See [Set interpolations](#bkmk_interpolation) for details.|  
-| functions > magnitude | The magnitude scoring function is used to alter rankings based on the range of values for a numeric field. Some of the most common usage examples of this are: </br></br>"Star ratings:" Alter the scoring based on the value within the "Star Rating" field. When two items are relevant, the item with the higher rating will be displayed first. </br>"Margin:" When two documents are relevant, a retailer may wish to boost documents that have higher margins first. </br>"Click counts:" For applications that track click through actions to products or pages, you could use magnitude to boost items that tend to get the most traffic. </br>"Download counts:" For applications that track downloads, the magnitude function lets you boost items that have the most downloads.|  
+| functions > magnitude | The magnitude scoring function is used to alter rankings based on the range of values for a numeric field. Some of the most common usage examples of this are: </br></br>"Star ratings:" Alter the scoring based on the value within the "Star Rating" field. When two items are relevant, the item with the higher rating will be displayed first. </br>"Margin:" When two documents are relevant, a retailer might wish to boost documents that have higher margins first. </br>"Click counts:" For applications that track clickthrough actions to products or pages, you could use magnitude to boost items that tend to get the most traffic. </br>"Download counts:" For applications that track downloads, the magnitude function lets you boost items that have the most downloads.|  
 | functions > magnitude > boostingRangeStart | Sets the start value of the range over which magnitude is scored. The value must be an integer or floating-point number. For star ratings of 1 through 4, this would be 1. For margins over 50%, this would be 50.|  
 | functions > magnitude > boostingRangeEnd | Sets the end value of the range over which magnitude is scored. The value must be an integer or floating-point number. For star ratings of 1 through 4, this would be 4.|  
 | functions > magnitude > constantBoostBeyondRange | Valid values are true or false (default). When set to true, the full boost will continue to apply to documents that have a value for the target field that’s higher than the upper end of the range. If false, the boost of this function won’t be applied to documents having a value for the target field that falls outside of the range.|  
@@ -239,10 +239,10 @@ Interpolations allow you to set the shape of the slope used for scoring. Because
 
 | Interpolation | Description |  
 |-|-|  
-|`linear`|For items that are within the max and min range, the boost applied to the item will be done in a constantly decreasing amount. Linear is the default interpolation for a scoring profile.|  
-|`constant`|For items that are within the start and ending range, a constant boost will be applied to the rank results.|  
-|`quadratic`|In comparison to a Linear interpolation that has a constantly decreasing boost, Quadratic will initially decrease at smaller pace and then as it approaches the end range, it decreases at a much higher interval. This interpolation option isn't allowed in tag scoring functions.|  
-|`logarithmic`|In comparison to a Linear interpolation that has a constantly decreasing boost, Logarithmic will initially decrease at higher pace and then as it approaches the end range, it decreases at a much smaller interval. This interpolation option isn't allowed in tag scoring functions.|  
+|`linear`|For items that are within the max and min range, boosting is applied in a constantly decreasing amount. Linear is the default interpolation for a scoring profile.|  
+|`constant`|For items that are within the start and ending range, a constant boost is applied to the rank results.|  
+|`quadratic`|In comparison to a linear interpolation that has a constantly decreasing boost, Quadratic initially decreases at smaller pace and then as it approaches the end range, it decreases at a much higher interval. This interpolation option isn't allowed in tag scoring functions.|  
+|`logarithmic`|In comparison to a linear interpolation that has a constantly decreasing boost, logarithmic initially decreases at higher pace and then as it approaches the end range, it decreases at a much smaller interval. This interpolation option isn't allowed in tag scoring functions.|  
 
  ![Constant, linear, quadratic, log10 lines on graph](media/scoring-profiles/azuresearch_scorefunctioninterpolationgrapht.png "AzureSearch_ScoreFunctionInterpolationGrapht")  
 

articles/search/toc.yml

@@ -411,12 +411,12 @@ items:
       href: semantic-how-to-enable-disable.md      
     - name: Configure semantic ranking
       href: semantic-how-to-configure.md
-    - name: Configure BM25 ranking
-      href: index-ranking-similarity.md
     - name: Add semantic ranking to queries
       href: semantic-how-to-query-request.md
     - name: Add a scoring profile
       href: index-add-scoring-profiles.md
+    - name: Configure BM25 ranking
+      href: index-ranking-similarity.md
   - name: Security
     items:
     - name: Configure network access