Remove link to Personalize compare search results and reorganize topic (

#4721) (#4723)

(cherry picked from commit a214fa7)

Signed-off-by: Fanit Kolchina <[email protected]>
Signed-off-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

_search-plugins/search-relevance/index.md

@@ -108,18 +108,12 @@ You cannot save a given comparison for future use, so Compare Search Results is
 
 One use case for Compare Search Results is the comparison of raw OpenSearch results with the same results processed by a reranking application. OpenSearch currently integrates with the following two rerankers:
 
-- [Amazon Personalize Search Ranking](#personalizing-search-results-with-amazon-personalize-search-ranking)
 - [Kendra Intelligent Ranking for OpenSearch](#reranking-results-with-kendra-intelligent-ranking-for-opensearch)
-
-### Personalizing search results with Amazon Personalize Search Ranking
-
-An example of a reranker is **Amazon Personalize Search Ranking**, contributed by the Amazon Personalize team. Amazon Personalize uses machine learning (ML) techniques to generate custom recommendations for your users. The plugin takes search results from OpenSearch and applies a [search pipeline]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/index/) to rerank them according to their Amazon Personalize ranking. The Amazon Personalize rankings are based on the user's past behavior and metadata about the search items and the user. This workflow improves the search experience for your users by personalizing their search results.
-
-To try Amazon Personalize Search Ranking, you must first set up Amazon Personalize. To get started, see [Amazon Personalize](https://docs.aws.amazon.com/personalize/latest/dg/setup.html). For detailed information, including plugin setup instructions, see [Personalizing search results from OpenSearch (self-managed)](https://docs.aws.amazon.com/personalize/latest/dg/personalize-opensearch.html).
+- [Amazon Personalize Search Ranking](#personalizing-search-results-with-amazon-personalize-search-ranking)
 
 ### Reranking results with Kendra Intelligent Ranking for OpenSearch
 
-Another example of a reranker is **Kendra Intelligent Ranking for OpenSearch**, contributed by the Amazon Kendra team. This plugin takes search results from OpenSearch and applies Amazon Kendra’s semantic relevance rankings calculated using vector embeddings and other semantic search techniques. For many applications, this provides better result rankings.
+An example of a reranker is **Kendra Intelligent Ranking for OpenSearch**, contributed by the Amazon Kendra team. This plugin takes search results from OpenSearch and applies Amazon Kendra’s semantic relevance rankings calculated using vector embeddings and other semantic search techniques. For many applications, this provides better result rankings.
 
 To try Kendra Intelligent Ranking, you must first set up the Amazon Kendra service. To get started, see [Amazon Kendra](https://aws.amazon.com/kendra/). For detailed information, including plugin setup instructions, see [Intelligently ranking OpenSearch (self managed) results using Amazon Kendra](https://docs.aws.amazon.com/kendra/latest/dg/opensearch-rerank.html).
 
@@ -173,4 +167,8 @@ The following example searches for the text "snacking nuts" in the `abo` index.
     In the preceding query, `body_field` refers to the body field of the documents in the index, which Kendra Intelligent Ranking uses to rank the results. The `body_field` is required, while the `title_field` is optional.
 1. Select **Search** and compare the results in **Result 1** and **Result 2**.
 
-For an example walkthrough with Amazon Personalize, see [Comparing OpenSearch results with results from the plugin](https://docs.aws.amazon.com/personalize/latest/dg/opensearch-comparing-results.html).
+### Personalizing search results with Amazon Personalize Search Ranking
+
+Another example of a reranker is **Amazon Personalize Search Ranking**, contributed by the Amazon Personalize team. Amazon Personalize uses machine learning (ML) techniques to generate custom recommendations for your users. The plugin takes search results from OpenSearch and applies a [search pipeline]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/index/) to rerank them according to their Amazon Personalize ranking. The Amazon Personalize rankings are based on the user's past behavior and metadata about the search items and the user. This workflow improves the search experience for your users by personalizing their search results.
+
+To try Amazon Personalize Search Ranking, you must first set up Amazon Personalize. To get started, see [Amazon Personalize](https://docs.aws.amazon.com/personalize/latest/dg/setup.html). For detailed information, including plugin setup instructions, see [Personalizing search results from OpenSearch (self-managed)](https://docs.aws.amazon.com/personalize/latest/dg/personalize-opensearch.html).