SIGIR LiveRAG Challenge Report
This year’s SIGIR conference featured the “LiveRAG Challenge”. In this competition participants received 500 questions synthesized from a given corpus (FineWeb10BT) and had 2 hours time to generate answers…
This year’s SIGIR conference featured the “LiveRAG Challenge”. In this competition participants received 500 questions synthesized from a given corpus (FineWeb10BT) and had 2 hours time to generate answers…
Are your users searching for particular brands? Can we use LLMs for brand detection and use this to improve search & drive business?
Enterprises and others building AI face some difficult choices – but there are already many with skills and experience to help!
How can generative AI help your customers find the right product by extracting information from reviews?
Human ratings for relevance tuning are resource-intensive to generate – so could we use a large language model like GPT instead?
A guest post from the Metarank team write on field boosts, Learning to Boost and Learning to Rank
Vector search & neural search – what exactly are these new techniques, what can they do and what do you need to consider when implementing them?
How to classify movies based on trending topics using a zero-shot classifier, Kubernetes and Apache Flink
A relevance engineer is a key, and often missing component of the search team, implementing information retrieval algorithms that solve user information needs in real time, at scale.
This article is been a bit late, but better late than never. Activate was a fantastic conference, and Lucidworks and the Montreal Sheraton were gracious hosts. These are a…
We’ve focused most of our conversation about machine learning and search on Learning to Rank (LTR), but LTR isn’t the only machine learning tool in the Solr/Elasticsearch toolbox. LTR…
Many organizations find relevance testing frustrating. Often we start consulting engagements and the first problem we have to solve is “how do we test search relevance?” In this article…