Past Talks
Browse the collection of talks from previous Haystack conferences
Using Vector Databases to Scale Multimodal Embeddings, Retrieval and Generation
Zain Hasan • Haystack EU 2023
How my team moved Search from the #1 to #7 challenge to solve, without changing relevance
Stéphane Renault • Haystack EU 2023
Strategies for using alternative queries to mitigate zero results and their application to online marketplaces
René Kriegler and Jean Silva • Haystack EU 2023
Reciprocal Rank Fusion (RRF) or How to Stop Worrying about Boosting
Philipp Krenn • Haystack EU 2023
Mastering Hybrid Search: Blending Classic Ranking Functions with Vector Search for Superior Search Relevance
Ohad Levi • Haystack EU 2023
Break, Learn, Refine – The Art of Hypothesis-Driven Development of ML-Powered Search
Andrey Kulagin • Haystack EU 2023
A Practical Approach for Few Shot Learning with SetFit for Scaling Up Search and Relevance Ranking on a Large Text Database
Fernando Vieira da Silva • Haystack EU 2023
Beyond the known: exploratory and diversity search with vector embeddings
Kacper Łukawski • Haystack EU 2023
Multilingual Search Support in European E-commerce: A Journey with Apache Lucene
Lucian Precup • Haystack EU 2023
Learning to hybrid search: combining BM25, neural embeddings and customer behavior into an ultimate ranking ensemble
Roman Grebennikov • Haystack US 2023
Talking to Non-Searchers about Search Relevance
David Tippett and Stavros Macrakis • Haystack US 2023
Exploiting Citation Networks in Large Corpora to Improve Relevance on Broad Queries
Marc-André Morissette • Haystack US 2023
Women of Search present Building Recommendation Systems with Vector Search
Erika Cardenas • Haystack US 2023
Populating and leveraging semantic knowledge graphs to supercharge search
Chris Morley • Haystack US 2023
A practical approach to measuring the relevance and preventing regressions
Aline Paponaud and Roudy Khoury • Haystack EU 2022
Lowering the entry threshold for Neural Vector Search by applying Similarity Learning
Kacper Łukawski • Haystack EU 2022
Increasing relevant product recall through smart use of customer behavioral data
Eric Rongen and Jelmer Krauwer • Haystack EU 2022
Personalized Search - Building a prototype to infer the user's interest
Tom Burgmans • Haystack US 2022
Learning a Joint Embedding Representation for Image Search using Self Supervised Means
Sujit Pal • Haystack US 2022
An approach to modelling implicit user feedback for optimising e-commerce search
René Kriegler • Haystack US 2022
Engagement DCG vs Subject Matter Expert DCG - Evaluating the Wisdom of the Crowd
Doug Rosenoff • Haystack US 2022
Beyond precision and recall – ensuring 'aboutness' in topical classification using confidence scores
Mark Shewhart and Sophie Lagace and Kimberly Hoffbauer • Haystack US 2022
Big Vector Search - The Billion-Scale Approximate Nearest Neighbor Challenge
George Williams • Haystack US 2022
OpenSearch - Ecommerce Search & Discovery Platform- Powered by querqy
Anirudha Jadhav and Pratik Shenoy and Dr. Johannes Peter • Haystack US 2022
Script Scores and back again - A tale of merchandising algorithms in Elasticsearch
Nate Day • Haystack 2021
Learning to Boost - Logistic Regression to Optimize Elasticsearch Boosts
Nina Xu and Jenna Bellassai • Haystack 2021
What Do They Want? Optimizing Search When Users Enter Broad Terms
Lisa Kowalkowski • Haystack LIVE! 2020
How to start climbing the Relevance Mountain - and make sure you can keep climbing!
Anthony Groves • Haystack LIVE! 2020
Question Answering as Search - the Anserini Pipeline and Other Stories
Sujit Pal • Haystack LIVE! 2020
Context sensitive autocomplete suggestions using LSTM and Pair-wise learning
Dileep Kumar Patchigolla • Haystack LIVE! 2020
How to Build your Training Set for a Learning to Rank Project
Alessandro Benedetti • Haystack LIVE! 2020
Click logs and insights - Putting the search experts in your audience to work
Peter Dixon-Moses • Haystack/MICES/Berlin Buzzwords 2020
Top 10 Lessons learned in search projects the past 10 years
Jettro Coenradie • Haystack/MICES/Berlin Buzzwords 2020
Thought Vectors, Knowledge Graphs, and Curious Death(?) of Keyword Search
Trey Grainger • Haystack/MICES/Berlin Buzzwords 2020
Not all those who browse are lost - few-shot and zero-shot personalization for digital commerce using deep architectures.
Jacopo Tagliabue • Haystack/MICES/Berlin Buzzwords 2020
Improving precision of e-commerce search results to generate value for customers and business
Jens Kürsten • Haystack EU 2019
Search to Search recommendations (Collaborative Synonym and Spell corrections)
Sadat Anwar • Haystack EU 2019
How to Kill Two Birds with One Stone: Learning to Rank with Multiple Objectives
Alexey Kurennoy • Haystack EU 2019
Architectural considerations on search relevancy in the context of e-commerce
Johannes Peter • Haystack 2019
Embracing Diversity: Searching over Multiple Languages
Suneel Marthi & Jeff Zemerick • Haystack 2018
Making the case for human judgement relevance testing
Tara Diedrichsen and Tito Sierra • Haystack 2019
Query relaxation - a rewriting technique between search and recommendations
Rene Kriegler • Haystack 2019
Rated Ranking Evaluator: an Open Source Approach for Search Quality Evaluation
Alessandro Benedetti • Haystack 2019
Towards a Learning To Rank Ecosystem @ Snag - We've got LTR to work! Now what?
Xun Wang • Haystack 2019
From user actions to better rankings: Challenges of using search quality feedback for learning to rank
Agnes Van Belle • Haystack EU 2018
Search quality evaluation: tools and techniques
Torsten Köster & Fabian Klenk & René Kriegler • Haystack EU 2018
'A picture is worth a thousand words' - Approaches to search relevance scoring based on product data, including image recognition
René Kriegler • Haystack 2018
Bad Text, Bad Search: Evaluating Text Extraction with Apache Tika's tika-eval Module
Tim Allison • Haystack 2018
The Solr Synonyms Maze: Pros, Cons, and Pitfalls of Various Synonyms Usage Patterns
Bertrand Rigaldies • Haystack 2018