July 2017
Beginner to intermediate
715 pages
17h 3m
English
Content preview from Java: Data Science Made Easy
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Reranking with Lucene
In this chapter, we already mentioned that Lucene can be customized, and we already took a look at how to do preprocessing outside of Lucene and then seamlessly integrate the results in the Lucene workflow.
When it comes to reranking search results, the situation is more or less similar. The common approach to this is taking the Lucene ranking as is and retrieve the top 100 (or more) results. Then we take these already retrieved documents and apply the ranking model to this for reordering.
If we have such a reranking model, we need to make sure that we store all the data we used for training. In our case, it was a QueryDocumentPair class from which we extracted the relevance features. So let's create an index:
FSDirectory ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.