The Retrieve and Rank Application uses the Retrieve and Rank Service to help users find the most relevant information for their query by using a combination of search and machine learning algorithms to detect "signals" in the data. Built on top of Apache Solr, developers load their data into the service, train a machine learning model based on known relevant results, then leverage this model to provide improved results to their end users based on their question or query. Users summarize their question and submit it to the Retrieve and Rank Application. The system searches the corpus, and generates, scores and ranks the answers. The system presents the most relevant answers from the corpus to the user, who is spared the time and effort of enlisting the community to provide an answer.
For an introduction into Retrieve and Rank, and how it can help your business, see this video. Then, you can read this blog post for more information about the business need for the application, the process behind making it, and how using it can improve your results. Please note, this link allows you to quickly see the PDF. If you wish to click on any of the included links, please click the raw button to download a full functional copy. You can also use a running instance of the application.