fixed links and raised acrolinx scores

Author: HeidiSteen

articles/search/cognitive-search-quickstart-blob.md

@@ -187,7 +187,7 @@ When you're working in your own subscription, it's a good idea at the end of a p
 
 You can find and manage resources in the portal, using the **All resources** or **Resource groups** link in the left-navigation pane.
 
-If you use a free service, remember that you're limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit. 
+If you used a free service, remember that you're limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit. 
 
 ## Next steps
 

articles/search/search-add-autocomplete-suggestions.md

@@ -19,11 +19,11 @@ Search-as-you-type is a common technique for improving query productivity. In Az
 
 To implement these experiences in Azure AI Search:
 
-+ Add a `suggester` to an index schema
++ Add a `suggester` to an index schema.
 + Build a query that calls the [Autocomplete](/rest/api/searchservice/autocomplete) or [Suggestions](/rest/api/searchservice/suggestions) API on the request.
 + Add a UI control to handle search-as-you-type interactions in your client app. We recommend using an existing JavaScript library for this purpose.
 
-In Azure AI Search, autocompleted queries and suggested results are retrieved from the search index, from selected fields that you have registered with a suggester. A suggester is part of the index, and it specifies which fields will provide content that either completes a query, suggests a result, or does both. When the index is created and loaded, a suggester data structure is created internally to store prefixes used for matching on partial queries. For suggestions, choosing suitable fields that are unique, or at least not repetitive, is essential to the experience. For more information, see [Create a suggester](index-add-suggesters.md).
+In Azure AI Search, autocompleted queries and suggested results are retrieved from the search index, from selected fields that you register with a suggester. A suggester is part of the index, and it specifies which fields provide content that either completes a query, suggests a result, or does both. When the index is created and loaded, a suggester data structure is created internally to store prefixes used for matching on partial queries. For suggestions, choosing suitable fields that are unique, or at least not repetitive, is essential to the experience. For more information, see [Create a suggester](index-add-suggesters.md).
 
 The remainder of this article is focused on queries and client code. It uses JavaScript and C# to illustrate key points. REST API examples are used to concisely present each operation. For end-to-end code samples, see [Next steps](#next-steps).
 
@@ -41,11 +41,11 @@ POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2020-06-30
 
 The "suggesterName" gives you the suggester-aware fields used to complete terms or suggestions. For suggestions in particular, the field list should be composed of those that offer clear choices among matching results. On a site that sells computer games, the field might be the game title.
 
-The "search" parameter provides the partial query, where characters are fed to the query request through the jQuery Autocomplete control. In the above example, "minecraf" is a static illustration of what the control might have passed in.
+The "search" parameter provides the partial query, where characters are fed to the query request through the jQuery Autocomplete control. In the above example, "minecraf" is a static illustration of what the control might pass in.
 
-The APIs do not impose minimum length requirements on the partial query; it can be as little as one character. However, jQuery Autocomplete provides a minimum length. A minimum of two or three characters is typical.
+The APIs don't impose minimum length requirements on the partial query; it can be as little as one character. However, jQuery Autocomplete provides a minimum length. A minimum of two or three characters is typical.
 
-Matches are on the beginning of a term anywhere in the input string. Given "the quick brown fox", both autocomplete and suggestions will match on partial versions of "the", "quick", "brown", or "fox" but not on partial infix terms like "rown" or "ox". Furthermore, each match sets the scope for downstream expansions. A partial query of "quick br" will match on "quick brown" or "quick bread", but neither "brown" or "bread" by themselves would be match unless "quick" precedes them.
+Matches are on the beginning of a term anywhere in the input string. Given "the quick brown fox", both autocomplete and suggestions match on partial versions of "the", "quick", "brown", or "fox" but not on partial infix terms like "rown" or "ox". Furthermore, each match sets the scope for downstream expansions. A partial query of "quick br" will match on "quick brown" or "quick bread", but neither "brown" or "bread" by themselves would be a match unless "quick" precedes them.
 
 ### APIs for search-as-you-type
 
@@ -66,7 +66,7 @@ Responses are shaped by the parameters on the request:
 
 + For Suggestions, set [$select](/rest/api/searchservice/suggestions#query-parameters) to return fields containing unique or differentiating values, such as names and description. Avoid fields that contain duplicate values (such as a category or city).
 
-The following additional parameters apply to both autocomplete and suggestions, but are perhaps more necessary for suggestions, especially when a suggester includes multiple fields.
+The following parameters apply to both autocomplete and suggestions, but are more applicable to suggestions, especially when a suggester includes multiple fields.
 
 | Parameter | Usage |
 |-----------|-------|
@@ -76,9 +76,9 @@ The following additional parameters apply to both autocomplete and suggestions,
 
 ## Add user interaction code
 
-Auto-filling a query term or dropping down a list of matching links requires user interaction code, typically JavaScript, that can consume requests from external sources, such as autocomplete or suggestion queries against an Azure Search Cognitive index.
+Autofilling a query term or dropping down a list of matching links requires user interaction code, typically JavaScript, that can consume requests from external sources, such as autocomplete or suggestion queries against an Azure Search Cognitive index.
 
-Although you could write this code natively, it's much easier to use functions from existing JavaScript library, such as one of the following. 
+Although you could write this code natively, it's easier to use functions from existing JavaScript library, such as one of the following. 
 
 + [Autocomplete widget (jQuery UI)](https://jqueryui.com/autocomplete/) appears in the Suggestion code snippet. You can create a search box, and then reference it in a JavaScript function that uses the Autocomplete widget. Properties on the widget set the source (an autocomplete or suggestions function), minimum length of input characters before action is taken, and positioning.
 
@@ -141,11 +141,11 @@ source: "/home/suggest?highlights=true&fuzzy=true&",
 
 ### Suggest function
 
-If you are using C# and an MVC application, **HomeController.cs** file under the Controllers directory is where you might create a class for suggested results. In .NET, a Suggest function is based on the [SuggestAsync method](/dotnet/api/azure.search.documents.searchclient.suggestasync). For more information about the .NET SDK, see [How to use Azure AI Search from a .NET Application](search-howto-dotnet-sdk.md).
+If you're using C# and an MVC application, **HomeController.cs** file under the Controllers directory is where you might create a class for suggested results. In .NET, a Suggest function is based on the [SuggestAsync method](/dotnet/api/azure.search.documents.searchclient.suggestasync). For more information about the .NET SDK, see [How to use Azure AI Search from a .NET Application](search-howto-dotnet-sdk.md).
 
 The `InitSearch` method creates an authenticated HTTP index client to the Azure AI Search service. Properties on the [SuggestOptions](/dotnet/api/azure.search.documents.suggestoptions) class determine which fields are searched and returned in the results, the number of matches, and whether fuzzy matching is used. 
 
-For autocomplete, fuzzy matching is limited to one edit distance (one omitted or misplaced character). Note that fuzzy matching in autocomplete queries can sometimes produce unexpected results depending on index size and how it's sharded. For more information, see [partition and sharding concepts](search-capacity-planning.md#concepts-search-units-replicas-partitions-shards).
+For autocomplete, fuzzy matching is limited to one edit distance (one omitted or misplaced character). Fuzzy matching in autocomplete queries can sometimes produce unexpected results depending on index size and how it's sharded. For more information, see [partition and sharding concepts](search-capacity-planning.md#concepts-search-units-replicas-partitions-shards).
 
 ```csharp
 public async Task<ActionResult> SuggestAsync(bool highlights, bool fuzzy, string term)

articles/search/search-api-preview.md

@@ -25,15 +25,15 @@ Preview features are removed from this list if they're retired or transition to
 | [**Import and vectorize data**](search-get-started-portal-import-vectors.md) | Azure portal | A wizard that creates a full indexing pipeline that includes data chunking and vectorization. The wizard creates all of the objects and configuration settings. | Available on all search services, in all regions. |
 | [**AzureOpenAIEmbedding skill**](cognitive-search-skill-azure-openai-embedding.md) | AI enrichment (skills) | A new skill type that calls Azure OpenAI embedding model to generate embeddings during queries and indexing. | [Create or Update Skillset (preview)](/rest/api/searchservice/preview-api/create-or-update-skillset), 2023-10-01-Preview or later. Also available in the portal through the [Import and vectorize data wizard](search-get-started-portal-import-vectors.md). |
 | [**Text Split skill**](cognitive-search-skill-textsplit.md) | AI enrichment (skills) | Text Split has two new chunking-related properties in preview: `maximumPagesToTake`, `pageOverlapLength`. | [Create or Update Skillset (preview)](/rest/api/searchservice/preview-api/create-or-update-skillset), 2023-10-01-Preview or later. Also available in the portal through the [Import and vectorize data wizard](search-get-started-portal-import-vectors.md). |
-| [**Index projections**](index-projections-concept-intro) | AI enrichment (skills) | A component of a skillset definition that defines the shape of a secondary index, supporting a one-to-many index pattern, where content from an enrichment pipeline can target multiple indexes.| [Create or Update Skillset (preview)](/rest/api/searchservice/preview-api/create-or-update-skillset), 2023-10-01-Preview or later. Also available in the portal through the [Import and vectorize data wizard](search-get-started-portal-import-vectors.md). |
+| [**Index projections**](index-projections-concept-intro.md) | AI enrichment (skills) | A component of a skillset definition that defines the shape of a secondary index, supporting a one-to-many index pattern, where content from an enrichment pipeline can target multiple indexes.| [Create or Update Skillset (preview)](/rest/api/searchservice/preview-api/create-or-update-skillset), 2023-10-01-Preview or later. Also available in the portal through the [Import and vectorize data wizard](search-get-started-portal-import-vectors.md). |
 |  [**Azure Files indexer**](search-file-storage-integration.md) | Indexer data source | New data source for indexer-based indexing from [Azure Files](https://azure.microsoft.com/services/storage/files/) | [Create or Update Data Source (preview)](/rest/api/searchservice/preview-api/create-or-update-data-source), 2021-04-30-Preview or later. |
 | [**SharePoint Indexer**](search-howto-index-sharepoint-online.md) | Indexer data source | New data source for indexer-based indexing of SharePoint content. | [Sign up](https://aka.ms/azure-cognitive-search/indexer-preview) to enable the feature. Use [Create or Update Data Source (preview)](/rest/api/searchservice/preview-api/create-or-update-data-source), 2020-06-30-Preview or later, or the Azure portal. |
 |  [**MySQL indexer**](search-howto-index-mysql.md) | Indexer data source | New data source for indexer-based indexing of Azure MySQL data sources.| [Sign up](https://aka.ms/azure-cognitive-search/indexer-preview) to enable the feature. Use [Create or Update Data Source (preview)](/rest/api/searchservice/preview-api/create-or-update-data-source), 2020-06-30-Preview or later, [.NET SDK 11.2.1](/dotnet/api/azure.search.documents.indexes.models.searchindexerdatasourcetype.mysql), and Azure portal. |
 | [**Azure Cosmos DB for MongoDB indexer**](search-howto-index-cosmosdb.md) | Indexer data source | New data source for indexer-based indexing through the MongoDB APIs in Azure Cosmos DB. | [Sign up](https://aka.ms/azure-cognitive-search/indexer-preview) to enable the feature. Use [Create or Update Data Source (preview)](/rest/api/searchservice/preview-api/create-or-update-data-source), 2020-06-30-Preview or later, or the Azure portal.|
 | [**Azure Cosmos DB for Apache Gremlin indexer**](search-howto-index-cosmosdb.md) | Indexer data source | New data source for indexer-based indexing through the Apache Gremlin APIs in Azure Cosmos DB. | [Sign up](https://aka.ms/azure-cognitive-search/indexer-preview) to enable the feature. Use [Create or Update Data Source (preview)](/rest/api/searchservice/preview-api/create-or-update-data-source), 2020-06-30-Preview or later.|
 | [**Native blob soft delete**](search-howto-index-changed-deleted-blobs.md) | Indexer data source | Applies to the Azure Blob Storage indexer. Recognizes blobs that are in a soft-deleted state, and removes the corresponding search document during indexing. | [Create or Update Data Source (preview)](/rest/api/searchservice/preview-api/create-or-update-data-source), 2020-06-30-Preview or later. |
 | [**Reset Documents**](search-howto-run-reset-indexers.md) | Indexer | Reprocesses individually selected search documents in indexer workloads. | [Reset Documents (preview)](/rest/api/searchservice/preview-api/reset-documents), 2020-06-30-Preview or later. |
-| [**speller**](speller-how-to-add) | Query | Optional spelling correction on query term inputs for simple, full, and semantic queries. | [Search Documents (preview)](/rest/api/searchservice/preview-api/search-documents), 2020-06-30-Preview or later, and Search Explorer (portal). |
+| [**speller**](speller-how-to-add.md) | Query | Optional spelling correction on query term inputs for simple, full, and semantic queries. | [Search Documents (preview)](/rest/api/searchservice/preview-api/search-documents), 2020-06-30-Preview or later, and Search Explorer (portal). |
 | [**Normalizers**](search-normalizers.md) | Query |  Normalizers provide simple text preprocessing: consistent casing, accent removal, and ASCII folding, without invoking the full text analysis chain.| [Search Documents (preview)](/rest/api/searchservice/preview-api/search-documents), 2020-06-30-Preview or later.|
 | [**featuresMode parameter**](/rest/api/searchservice/preview-api/search-documents#query-parameters) | Relevance (scoring) | Relevance score expansion to include details: per field similarity score, per field term frequency, and per field number of unique tokens matched. You can consume these data points in [custom scoring solutions](https://github.com/Azure-Samples/search-ranking-tutorial). | [Search Documents (preview)](/rest/api/searchservice/preview-api/search-documents), 2019-05-06-Preview or later.|
 | [**Azure Machine Learning (AML) skill**](cognitive-search-aml-skill.md) | AI enrichment (skills) | A new skill type to integrate an inferencing endpoint from Azure Machine Learning. | [Create or Update Skillset (preview)](/rest/api/searchservice/preview-api/create-or-update-skillset), 2019-05-06-Preview or later. Also available in the portal, in skillset design, assuming Azure AI Search and Azure Machine Learning services are deployed in the same subscription. |

articles/search/search-indexer-howto-access-private.md

@@ -266,7 +266,7 @@ A `202 Accepted` response is returned on success. The process of creating an out
 
 ## 2 - Approve the private endpoint connection
 
-Approval of the private endpoint connection is granted on the Azure PaaS side. It might be automatic if the service consumer has Azure role-based access control (RBAC) permissions on the service provider resource. Otherwise, manual approval is required. For details, see [Manage Azure private endpoints](/azure/private-link/manage-private-endpoint).
+Approval of the private endpoint connection is granted on the Azure PaaS side. It might be automatic if the service consumer has a role assignment on the service provider resource. Otherwise, manual approval is required. For details, see [Manage Azure private endpoints](/azure/private-link/manage-private-endpoint).
 
 This section assumes manual approval and the portal for this step, but you can also use the REST APIs of the Azure PaaS resource. [Private Endpoint Connections (Storage Resource Provider)](/rest/api/storagerp/privateendpointconnections) and [Private Endpoint Connections (Cosmos DB Resource Provider)](/rest/api/cosmos-db-resource-provider/2023-03-15/private-endpoint-connections) are two examples.