recommendation
Open source recommendation system based on time-series data and statistical analysis. Written in TypeScript
and Node.js
using Redis
for storage. The recommendation system uses the Jaccard index
to calculate the intersection between two sets. One set is represented by the maximum possible sum of tag score and the other set is the score sum of user events per tag. The higher the Jaccard index, the higher the recommendation. It uses numbers to represent sets to increase performance.
Features
- Use tag score and Jaccard index
- Content-based filtering
- Event-driven powered engine
- Naive exploration of new tags
- Suitable for product and content recommendation
- Fine-tuning of tag weights
- Minimalist and lightweight
- Written in TypeScript and Node.js
Overview video
How it works
How the data is stored:
- Actors are stored in Redis as simple
String
keys with create datetimestamps
as value. - Items are
Set
type withtags
as members. The item may have…