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Ex Libris ‘bX’ Recommender Promo Video October 5, 2010

Posted by Andre Vellino in Collaborative filtering, Recommender.

I stumbled across this Ex Libris promo video for its ‘bX’ recommender yesterday. Having done quite a few of these use-case demo scenarios to “show the value”, I appreciate how hard it is to pitch a relatively complex idea in straight-forward terms. I think it does a pretty good job too, notwithstanding the slightly over-the-top-happiness tenor of the whole thing.

At the risk of repeating myself, though, there’s one thing that the video glosses over.  SFX logs are, effectively, click-logs and clicks have two sources: search engine results and ‘bX’ recommendations themselves.  Hence ‘bX’ recommendations are more likely to be “semantically homogenous” (although less so than pure search results) because the data they derive from is biased by search-engine ranking.  The proportion of SFX trafic that is generated by the recommender itself further narrows the semantic diversity of recommendations.


1. The Trove Rove - December 15, 2011

Thanks for posting this critical analysis of the bX Recommender Service. In doing research on the service, it has been helpful to finally find critiques to balance the accolades.

2. Andre Vellino - December 15, 2011

Thanks for your comment on my blog post. Sometimes you don’t realize people are reading / listening.

In the blog post I should have pointed to this article I wrote for ASIST last year which summarizes a short study I did comparing ‘bX’ and another, citation-based recommender system I developed.


You can try the web-application that shows the different recommendations side-by-side on this web site:


Just search for something and the results will show you those items for which there are either ‘bX’ recommendations, citation-based recommendations or both (via a color-coded “Recommendations” button).

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