Over the summer I served as a Google Summer of Code mentor for David Nemeskey, PhD student at Eötvös Loránd University. David proposed to improve Lucene’s scoring architecture and implement some state-of-the-art ranking models with the new framework.
These improvements are now committed to Lucene’s trunk: you can use these models in tandem with all of Lucene’s features (boosts, slops, explanations, etc) and queries (term, phrase, spans, etc). A JIRA issue has been created …
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This is part 10 in a (never ending?) series of articles on Indexing and Searching the ISFDB.org data using Solr.
Circumstances have conspired to keep my away from this series longer then I had intended, So today I want to jump right in talking about improving the user experience by improving relevancy.
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A big chunk of the billions that go to search-engine marketing and search engine optimization, SEM and SEO, (mostly to you-know-who) are spent on getting to Page 1 of the results.
I won’t be the first to point out that relevance for in-house search — i.e., without using Pagerank — is a harder nut to crack. How much harder? A recent study from Aberdeen Group, publicized this week in Information Week, provides the following …
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