From 40dba03e2e2d795d8da315ed547d2ddf0f5e16d5 Mon Sep 17 00:00:00 2001 From: Filip Makraduli <73337655+fm1320@users.noreply.github.com> Date: Sun, 19 Oct 2025 22:03:34 +0100 Subject: [PATCH] Update airbnb-search-benchmarking.md --- docs/articles/airbnb-search-benchmarking.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/articles/airbnb-search-benchmarking.md b/docs/articles/airbnb-search-benchmarking.md index f229ddbb1..ec3aa0787 100644 --- a/docs/articles/airbnb-search-benchmarking.md +++ b/docs/articles/airbnb-search-benchmarking.md @@ -8,7 +8,7 @@ Converting a mental image of a luxury apartment near the city's finest cafés or Motivated by this challenge of bridging unstructured user intent with structured listing attributes, in this article, we evaluate a range of retrieval techniques from classic keyword-matching approaches through vector search, hybrid, multi-vector strategies, and ultimately Superlinked's semantic engine using a mixture of encoders. -While traditional search systems often treat structured data (like price, and rating) as simple filters and unstructured data (like descriptions) as separate search indices, our benchmark reveals how modern approaches can understand the semantic relationships between all attribute types. By comparing various methodologies on the same Airbnb dataset, we quantify the advantages of integrated approaches like Superlinked's mixture of encoders, which can understand that 'affordable with good reviews' represents both a price range and quality expectation rather than just matching keywords. This benchmark provides actionable insights for developers looking to implement more intuitive search experiences across domains with mixed data types. +While traditional search systems often treat structured data (like price, and rating) as simple filters and unstructured data (like descriptions) as separate search indices, our benchmark reveals how modern approaches can understand the semantic relationships between all attribute types. By comparing various methodologies on the same Airbnb dataset, we quantify the advantages of integrated approaches like Superlinked's mixture of encoders, which can understand that 'affordable with good reviews' represents both a price range and quality expectation rather than just matching keywords. This benchmark provides actionable insights for developers looking to implement more intuitive search experiences across domains with mixed data types. If you want to test out Superlinked's approach on your own data, feel free to [talk to us!](https://links.superlinked.com/airbnb_bench). ## Data Exploration: Stockholm Airbnb Listings