Skip to content

Commit c4472c2

Browse files
committed
Updated search-get-started-portal-image-search.md
1 parent 542e148 commit c4472c2

File tree

1 file changed

+3
-3
lines changed

1 file changed

+3
-3
lines changed

articles/search/search-get-started-portal-image-search.md

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -400,9 +400,9 @@ When the wizard completes the configuration, it creates the following objects:
400400
401401
## Check results
402402

403-
This quickstart creates a multimodal index that supports [hybrid search](hybrid-search-overview.md) over both text and images. Unless you use direct multimodal embeddings, the index doesn't accept images as query inputs, which requires the [AML skill](cognitive-search-aml-skill.md) or [Azure AI Vision multimodal embeddings skill](cognitive-search-skill-vision-vectorize.md) with an equivalent vectorizer. For more information, see [Query with Search explorer](search-explorer.md).
403+
This quickstart creates a multimodal index that supports [hybrid search](hybrid-search-overview.md) over both text and images. Unless you use direct multimodal embeddings, the index doesn't accept images as query inputs, which requires the [AML skill](cognitive-search-aml-skill.md) or [Azure AI Vision multimodal embeddings skill](cognitive-search-skill-vision-vectorize.md) with an equivalent vectorizer. For more information, see [Configure a vectorizer in a search index](vector-search-how-to-configure-vectorizer.md).
404404

405-
Hybrid search is a combination of full-text queries and vector queries. When you issue a hybrid query, the search engine computes the semantic similarity between your query and the indexed vectors and ranks the results accordingly. For the index created in this quickstart, the results surface content from the `content_text` field that closely aligns with your query.
405+
Hybrid search is combines full-text queries and vector queries. When you issue a hybrid query, the search engine computes the semantic similarity between your query and the indexed vectors and ranks the results accordingly. For the index created in this quickstart, the results surface content from the `content_text` field that closely aligns with your query.
406406

407407
To query your multimodal index:
408408

@@ -430,7 +430,7 @@ This quickstart uses billable Azure resources. If you no longer need the resourc
430430

431431
## Next steps
432432

433-
This quickstart introduced you to the **Import and vectorize data wizard**, which creates all of the necessary objects for multimodal search. To explore each step in detail, see the following tutorials:
433+
This quickstart introduced you to the **Import and vectorize data** wizard, which creates all of the necessary objects for multimodal search. To explore each step in detail, see the following tutorials:
434434

435435
+ [Tutorial: Image verbalization and Document Extraction skill](tutorial-document-extraction-image-verbalization.md)
436436
+ [Tutorial: Image verbalization and Document Layout skill](tutorial-document-layout-image-verbalization.md)

0 commit comments

Comments
 (0)