Join us to see how we implemented boosting personalized search results and reengineered the legacy solution.
We have achieved 40 - 60% less effort by our users to find the content they are looking for among 40 million documents within 100 - 200 milliseconds including search, popularity, personalization times. The average number of letters used in searches decreased from 9 to 4.
In this live coding session, we will go over following items
- Elasticsearch : basics, analyzers, char filters, token filters
- ranking based boosting
- personalized (behavior based) boosting
- Kafka : real time user profile generation
- Spring Boot : put them all together