Query Suggestions with Manticore Search

Query Suggestions is a powerful feature that comes built-in with Manticore Search.*

*Available in preview release

What is Query Suggestions

Query Suggestions provide possible search queries as users type, similar to how Google predicts searches in its search box. Manticore Search offers this feature right out of the box, making it easy to integrate.

What is it
When to use

When you need Query Suggestions

  • Enhancing user search experience
  • Helping users discover related content
  • Correcting typos in search queries
  • Guiding users towards popular or trending searches
  • Assisting users in formulating more specific queries
  • Improving search relevancy and results
  • Analyzing user search patterns and behavior
  • Optimizing product discovery for e-commerce
  • Enhancing internal site search functionality

Why Manticore Search is good for Query Suggestions

  • It’s readily available with Manticore Search; simply install and use the CALL AUTOCOMPLETE SQL statement or /autocomplete JSON endpoint to start generating query suggestions.
  • Manticore Search offers flexible configuration options to customize suggestions to your needs.
  • You can use both high-level methods like CALL AUTOCOMPLETE and low-level methods for advanced customization.

How to get started

Install Manticore Search

  1. Follow the installation instructions for your operating system.
  2. Alternatively, use Docker: docker pull manticoresearch/manticore:dev.

Prepare your Manticore Search table

  1. Create a table.
  2. Configure full-text fields and attributes.
  3. Index your data using the appropriate method (SQL, JSON, CSV, etc.).

Implement Query Suggestions

  1. Use the CALL AUTOCOMPLETE SQL statement or /autocomplete JSON endpoint to get query suggestions.
  2. Implement a client-side request to query Manticore Search.
  3. Process the response and present suggestions to the user.

Optimize your Query Suggestions

  1. Pass additional parameters to the CALL AUTOCOMPLETE function, such as expansion_len, fuzziness, append, prepend, layouts, etc.
  2. Use fuzziness to control the level of fuzzy matching in suggestions.

Leverage Query Suggestions

  1. Enjoy powerful and efficient query suggestions with Manticore Search.
  2. If you encounter any issues, report them on GitHub.
  3. Consider our professional services for advanced implementation and optimization.

Manticore Search Logo Pros

  • Easy-to-use, built-in method: CALL AUTOCOMPLETE SQL or /autocomplete JSON query.
  • Flexible configuration options for fine-tuning suggestions.
  • Supports both exact and fuzzy matching.
  • Efficient performance on various dataset sizes.
  • Ability to reject unwanted suggestions.
  • Compatible with both SQL and JSON interfaces.
  • Manticore Search Logo Cons

  • May require careful tuning for optimal results on very large datasets.
  • Suggestions are based on indexed data, requiring regular updates to keep content fresh.
  • Advanced customization might require a deep understanding of underlying algorithms.
  • Learn more about other use cases

    Do not stop here when learning when you need Query Suggestions and how Manticore Search can help you. There are many other use cases that you can explore.

    Get Started with Query Suggestions in Manticore Search

    Enhance your search functionality with Query Suggestions today!

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