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

Testing tool to verify the search qualities of the Elasticsearch indices

Tools to help search relevance engineers and business users tune search results for their OpenSearch applications.

Solr Relevance Ranking Analysis and Visualization Tool

Optimize and Enhance Your Search Quality

An open source tool to measure search relevance.

First assessment of learning-to-rank: testing machine-learned ranking of search results on English Wikipedia

Search Relevance Surveys and Deep Learning: Turning Noisy, Crowd-sourced Opinions Into An Accurate Relevance Judgement (T175048)

A quick hack, for now, to recollect expert based judgmenet for search

The 3rd place solution code for the Wikipedia - Image/Caption Matching Competition on Kaggle

Search relevancy algorithm for news articles using Sentence-BERT model and ANNOY library along with deployment on AWS using Docker.

Measure relevance of search result for CrowdFlower, an ecomerce site. Model trained was SVC

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.

Exploring search relevance techniques.