There are 1 repository under search-relevance topic.
1st Place Solution for CrowdFlower Product Search Results Relevance Competition on Kaggle.
Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch
3rd Place Solution for HomeDepot Product Search Results Relevance Competition on Kaggle.
Query preprocessor for Java-based search engines (Querqy Core and Solr implementation)
Framework for building Commerce Search Solutions around open source search technology like Elasticsearch
Tools to help search relevance engineers and business users tune search results for their OpenSearch applications.
Solr Relevance Ranking Analysis and Visualization Tool
An open source tool to measure search relevance.
Search Relevance Surveys and Deep Learning: Turning Noisy, Crowd-sourced Opinions Into An Accurate Relevance Judgement (T175048)
First assessment of learning-to-rank: testing machine-learned ranking of search results on English Wikipedia
Search relevancy algorithm for news articles using Sentence-BERT model and ANNOY library along with deployment on AWS using Docker.
The 3rd place solution code for the Wikipedia - Image/Caption Matching Competition on Kaggle
A quick hack, for now, to recollect expert based judgmenet for search
Measure relevance of search result for CrowdFlower, an ecomerce site. Model trained was SVC
Exploring search relevance techniques.
In this repo, I attempt to quantify the search relevance of different query settings using the Normalized Discounted Cumulative Gain (NDCG).
Enhance the performance and cost-efficiency of large-scale Retrieval Augmented Generation (RAG) applications. Learn to integrate vector search with traditional database operations and apply techniques like prefiltering, postfiltering, projection, and prompt compression.