Frequently Bought Together Overview

AddSearch's Frequently Bought Together (FBT) feature recommends sets of products or documents that users often purchase or view together. This can help you suggest related news articles, complementary products, or other grouped items.

How It Works

FBT relies on the FP-growth algorithm, a frequent-pattern mining method. It discovers frequently occurring itemsets efficiently by building a frequent pattern tree (FP-tree).

Setting Up Frequently Bought Together

1. Upload your data:

   • Add your dataset via the AddSearch dashboard.
   • Or push the dataset using the Indexing API.
   • See Uploading FBT recommendation data for details.

2. Configure recommendations:

   • Define how FBT recommendations should behave.
   • Refer to Configuring FBT recommendations for configuration steps.

Implementing FBT Recommendations

You can integrate FBT recommendations using the AddSearch API or JavaScript libraries:

• Use the AddSearch API Get Recommendations endpoint to fetch FBT data.
• For JavaScript integration, use:
  • Search Client
  • Search UI library

These tools allow you to display frequently bought together items seamlessly within your website or app.

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For more details on each step, please refer to the linked documentation pages.