Boosting Document Rankings Using Search History
TLDR Jason inquired about boosting document rankings based on user search history. Jason explained it's achievable using the vector search feature of Typesense and suggested using a machine learning model before providing an API to demonstrate it.
Nov 29, 2022 (13 months ago)
Is this achievable?
Dec 29, 2022 (12 months ago)
Indexed 3015 threads (79% resolved)
Integrating Semantic Search with Typesense
Krish wants to integrate a semantic search functionality with typesense but struggles with the limitations. Kishore Nallan provides resources, clarifications and workarounds to the raised issues.
Optimizing Dataset of Podcast Feeds for a Searchable Database
Alexander seeks advice on optimizing a podcast database for search. Kishore Nallan suggests data size and stopwords impact RAM usage, and that benchmarking on 1M records would be useful. satish raises the potential need for vector searching. Both recommend feeding user activity data into ML models for relevancy ranking. Collaboration was suggested.
Typesense Query for Related Documents in Ecommerce
Vlassis asked about finding related documents using a Typesense query. Jason suggested using vector search and recommended ML libraries for vector generation, with 'word2vec' for text content. Vlassis agreed to try it out.