Smarter search using machine learning
Increasingly Solr and Elasticsearch teams rely on machine learning to solve their thorniest issues. Learning to Rank applies machine learning directly to search relevance. With the right plumbing in place, Learning to Rank can answer questions with remarkable accuracy, getting to the heart of what user's want.
As the leaders in search relevance and matching, OpenSource Connections builds Learning to Rank capabilities for some of the biggest names in search. We wrote the book on smarter search. We built the Elasticsearch Learning to Rank plugin currently used across the industry.
Leverage OpenSource Connections services to
- Evaluate your organization's readiness for Learning to Rank
- Determine how user behavioral data can be used for machine learning
- Explore which learning to rank model is right for you use cases
- Implement Learning to Rank with Solr or Elasticsearch
- Mentor your team to build your own relevance & learning to rank practice internally
Here's what clients have to say
We can't recommend OSC enough if you depend on search and want to make a significant impact on your business.
We leverage OSC’s deep expertise to solve relevance challenges unique to our industry. Partnering with OSC ensures that our scientific, technological, and medical publishing expertise and taxonomies are extended into the best-in-breed search technology that powers the targeted retrieval of our clients’ nuanced scholarly content.
OSC's Solr/Lucene knowledge expanded and greatly improved the abilities of our public job search. They delivered technical excellence at every turn: demonstrating expertise in Lucene internals, relevance models, and data science backed by a solid methodology for improving search relevance. On a deliverables front: they learned our legacy search stack quickly and made high-quality code contributions. OSC marries technical excellence with strategic insight: we highly recommend their experts to any search team.
I’ve rarely experienced such positive, results-oriented, cheerful customer service.
Our Learning to Rank products & publications:
Elasticsearch Learning to Rank Elasticsearch plugin that uses machine learning models for ranking results
Our latest relevance articles:
A guide on how to implement, test, and deploy a Normalized Discounted Cumulative Gain (NDCG) ranking quality scorer in Quepid....
The agenda for Haystack - the search relevance talk - has been announced!
Optimizing products to build real brand fanatics - beyond just 'conversions'.