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There is a vivid discussion about relevance ranking for library resources in discovery interfaces in recent years. In articles, blog posts and presentations on this topic, again and again possible ranking factors are discussed beyond well known term statistic based methods like the vector space retrieval model with tf*idf weighting (often after claiming term statistics based approaches wouldn't work on library data, of course without proofing that). Usually the following possible factors are mentioned: - popularity (often after stressing Google's success with PageRank), measured in several ways like holding quantities, circulation statistics, clicks in catalogues, explicit user ratings, number of citations, ... - freshness: rank newer items higher (ok, we have that in many old school Boolean OPACs as "sort by date", but not in combination with other ranking factors like term statistics) - availability - contextual/individual factors, eg. if (user.status=student) boost(textbook); if (user.faculty=economics) boost(Karl Marx); if season=christmas boost(gingerbread recipes); ... - ... I tried to find examples where such factors beyond term statistics are used to rank search results in libraryland. But I hardly find them, only lots of theoretical discussions about all the pros and cons of all thinkable factors going on since the 1980s. I mean, all that is doable with search engines like Solr today. But it seems, it is hardly implemented somewhere in real systems (beyond simple cases, for example we slightly boost hits in collections a user has immediate online access to, but we never asked users, if they like it or notice at all). WorldCat does a little bit something, it seems. They, of course, boost resources with local holdings in WorldCat local. And they use language preferences (Accept-Language HTTP header) for boosting titles in users' preferred languages. And there might be more in WorldCat ranking. But there is not much published on that, it seems? So, if you implemented something beyond term statistics based ranking, speak up and show. I am very interested in real world implementations and experiences (like user feedback, user studies etc.). Thanks, Till