[Search] Add search approaches content, rename querying-for-search doc

Author: leemthompo

raw-migrated-files/elasticsearch/elasticsearch-reference/full-text-filter-tutorial.md

@@ -196,7 +196,7 @@ At search time, {{es}} defaults to the analyzer defined in the field mapping. In
 }
 ```
 
-1. The `hits` object contains the total number of matching documents and their relation to the total. Refer to [Track total hits](../../../solutions/search/querying-for-search-searching-with-the-search-api.md#track-total-hits) for more details about the `hits` object.
+1. The `hits` object contains the total number of matching documents and their relation to the total. Refer to [Track total hits](../../../solutions/search/querying-for-search.md#track-total-hits) for more details about the `hits` object.
 2. `max_score` is the highest relevance score among all matching documents. In this example, we only have one matching document.
 3. `_score` is the relevance score for a specific document, indicating how well it matches the query. Higher scores indicate better matches. In this example the `max_score` is the same as the `_score`, as there is only one matching document.
 4. The title contains both "Fluffy" and "Pancakes", matching our search terms exactly.

raw-migrated-files/elasticsearch/elasticsearch-reference/search-analyze.md

@@ -29,7 +29,7 @@ Refer to [Query languages](../../../explore-analyze/query-filter.md#search-analy
 
 [Query DSL](../../../explore-analyze/query-filter/languages/querydsl.md) is a full-featured JSON-style query language that enables complex searching, filtering, and aggregations. It is the original and most powerful query language for {{es}} today.
 
-The [`_search` endpoint](../../../solutions/search/querying-for-search-searching-with-the-search-api.md) accepts queries written in Query DSL syntax.
+The [`_search` endpoint](../../../solutions/search/querying-for-search.md) accepts queries written in Query DSL syntax.
 
 
 #### Search and filter with Query DSL [search-analyze-query-dsl-search-filter]

raw-migrated-files/elasticsearch/elasticsearch-reference/search-with-elasticsearch.md

@@ -25,7 +25,7 @@ Vector search
 
 To run a search request, you can use the search API or Search Applications.
 
-[Search API](../../../solutions/search/querying-for-search-searching-with-the-search-api.md)
+[Search API](../../../solutions/search/querying-for-search.md)
 :   The [search API](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-search.html) enables you to search and [aggregate](../../../explore-analyze/aggregations.md) data stored in {{es}} using a query language called the [Query DSL](../../../explore-analyze/query-filter/languages/querydsl.md).
 
 [Search Applications](../../../solutions/search/applications.md)

solutions/search/querying-for-search-searching-with-the-search-api.md renamed to solutions/search/querying-for-search.md

@@ -8,7 +8,7 @@ mapped_urls:
   - https://www.elastic.co/guide/en/elasticsearch/reference/current/_retrievers_examples.html
 ---
 
-# Querying for search / searching with the search API
+# Query languages for search
 
 % What needs to be done: Lift-and-shift
 

solutions/search/search-approaches.md

@@ -1,5 +1,22 @@
 # Search approaches
 
-% What needs to be done: Write from scratch
+To deliver relevant search results, you need to choose the right search approach for your data and use case.
 
-% Scope notes: ml, full text, hybrid
+The following table provides an overview of the fundamental search techniques available in {{es}}:
+
+| Name | Description | Notes |
+|------|-------------|--------|
+| [**Full-text search**](full-text.md) | Traditional lexical search with analyzers and relevance tuning | Essential foundation for keyword matching, works out of the box |
+| [**Vector search**](vector.md) | Similarity search using numerical vectors | Requires extra setup/resources, ideal for finding similar documents |
+| [**Semantic search**](semantic-search.md) | Meaning-based search using natural language understanding | Requires ML models and vector infrastructure |
+| [**Hybrid search**](hybrid.md) | Combines lexical and vector/semantic approaches | Best balance for both keyword precision and semantic relevance |
+| [**Re-ranking**](semantic-reranking.md) | Post-processing results to improve relevance | Optional ML-based enhancement for fine-tuned relevance |
+| [**Geospatial search**](/explore-analyze/geospatial-analysis.md) | Location-based search and spatial relationships | For maps, distance calculations, and shape queries |
+
+:::::{tip}
+ Full-text search is a very powerful tool in itself. One of the key strengths of {{es}} is its flexibility, allowing you to start with full-text search and gradually incorporate more complex or resource-intensive approaches over time.
+:::::
+
+## Next step
+
+Once you've chosen your search approach(es), you'll need to select a query language to implement them. Refer to [query languages for search use cases]() to learn about the available options.

solutions/toc.yml

@@ -588,7 +588,7 @@ toc:
         children:
           - file: search/search-approaches/long-running-searches.md
           - file: search/search-approaches/near-real-time-search.md
-      - file: search/querying-for-search-searching-with-the-search-api.md
+      - file: search/querying-for-search.md
       - file: search/inference-api.md
         children:
           - file: search/inference-api/elastic-inference-service-eis.md