What is a recommendation engine?
A recommendation engine is an AI-powered data filtering tool that uses machine learning algorithms to suggest relevant items to users or customers. It analyzes patterns in consumer behavior data to make personalized recommendations. These engines are widely used by companies like Netflix, Amazon, and Google to enhance user experiences, drive sales, and increase engagement.
How does a recommendation engine work in AI search
A recommendation engine in AI search typically works through the following process:
- Data collection: This process gathers both implicit data (e.g., search history, clicks) and explicit data (e.g., ratings, reviews) from users.
- Data storage: Stores the collected data in scalable warehouses or lakes.
- Data analysis: Machine learning algorithms process and examine the data, identifying patterns and correlations.
- Filtering: Applies mathematical rules and formulas to filter the data based on the chosen recommendation method.
- Prediction and recommendation: Generates personalized user suggestions based on the analyzed and filtered data.
