Provide the insights about the important elements need to be considered for building an in-house recommendation system. How could maximize the usage of in-house reco engine. General introduction/summary about major methods/implementations of building recommendation system as well as the limitations/challenges of in-use algorithms.
Key Takeaways
- Recommendation system is basically a scoring system blended with ML results and business rules, need to have a balanced approach for scoring.
- Pre-set business targets, flexibility of code and continuously testing can maximize the usage of the engine.
- Platform, Integration, and the change of way of work matter
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