Azure AI Search Solution: Apply Filtering and Sorting

By Ashwin Venugopal -

 





Apply Filtering and Sorting

Users frequently like to filter and order query results according to field values in search solutions. Both of these features are supported by Azure AI Search via the search query API.

Filtering Results

You can apply filters to queries in two ways:

  1. By including filter criteria in a simple search expression.
  2. By providing an OData filter expression as a $filter parameter with a full syntax search expression.

You can apply a filter to any filterable field in the index.

Filtering With Facets

When presenting users with filtering criteria based on field values in a result set, facets are a helpful tool. They function best when a field contains a limited number of discrete values that can be shown in the user interface as options or links.

In order to use facets, you must first define the facetable fields for which you wish to extract the potential values.

Sorting Results

The query process's relevancy score is used by default to rank the results, with the highest scoring matches appearing first. Nevertheless, by adding an OData orderby option that identifies one or more sortable fields and a sort order (asc or desc), you can override this order.

Enhance Index

You may create an efficient search solution with a simple index and a client that can input queries and show results. Nonetheless, Azure AI Search offers a number of methods for improving an index to give users a better experience.

Search-as-you-type

To make it easier for users to obtain relevant results, you can enable two types of search-as-you-type experiences by adding a suggester to an index:

  • Suggestions - retrieve and display a list of suggested results as the user types into the search box, without needing to submit the search query.

  • Autocomplete - complete partially typed search terms based on values in index fields.

To implement one or both of these capabilities, create or update an index, defining a suggester for one or more fields.

You can utilize the suggestion and autocomplete REST API endpoints or the .NET DocumentsOperationsExtensions after adding a suggester.Make suggestions and record operations extensions.A list of recommended results or autocompleted terms to be displayed in the user interface can be obtained by submitting a partial search phrase using autocomplete methods.

Custom Scoring and Result Boosting

By default, a relevance score derived from the term frequency/inverse-document-frequency (TF/IDF) method is used to order search results.

By creating a scoring profile that assigns a weighting value to particular fields, basically raising the search score for documents when the search term appears in those fields, you may alter how this score is determined.

Additionally, you can boost results based on field values, for example, increasing the relevancy score for documents based on how recently they were modified or their file size. After you have defined a scoring profile, you can specify its use in an individual search, or you can modify an index definition so that it uses your custom scoring profile by default.

Synonyms

There are frequently several ways to refer to the same thing. For example, any of the following terms may be used by someone looking for information about the United Kingdom:

  1. United Kingdom
  2. UK
  3. Great Britain
  4. GB

You can create synonym maps that connect related terms to assist people in finding the information they require. When a user searches for a specific phrase, documents with fields containing the term or any of its synonyms will appear in the results. You can then apply those synonym mappings to individual fields in an index.

Conclusion

We have successfully learnt about applying filtering and sorting.





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