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Learning to Rank with Vespa – Getting started with Text Search

Vespa.ai have just published two tutorials to help people to get started with text search applications by building scalable solutions with Vespa. The tutorials were based on the full document...

E-commerce search and recommendation with Vespa.ai

Holiday shopping season is upon us and it’s time for a blog post on E-commerce search and recommendation using Vespa.ai. Vespa.ai is used as the search and recommendation backend at...

Vespa Product Updates, October/November 2019: Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance, and Datadog Monitoring Support

In the September Vespa product update, we mentioned Tensor Float Support, Reduced Memory Use for Text Attributes, Prometheus Monitoring Support, and Query Dispatch Integrated in Container.

Vespa Product Updates, September 2019: Tensor Float Support, Reduced Memory Use for Text Attributes, Prometheus Monitoring Support, and Query Dispatch Integrated in Container

In the August Vespa product update, we mentioned BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export. Largely developed by Yahoo engineers, Vespa is an open source...

Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export

In the recent Vespa product update, we mentioned Large Machine Learning Models, Multithreaded Disk Index Fusion, Ideal State Optimizations, and Feeding Improvements. Largely developed by Yahoo engineers, Vespa is an...

Vespa Product Updates, May 2019: Deploy Large Machine Learning Models, Multithreaded Disk Index Fusion, Ideal State Optimizations, and Feeding Improvements

In last month’s Vespa update, we mentioned Tensor updates, Query tracing and coverage. Largely developed by Yahoo engineers, Vespa is an open source big data processing and serving engine. It’s...