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Library Portals Survey March 14, 2007

Posted by Andre Vellino in Collaborative filtering, Digital library, Recommender service.
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Over the past couple of months, I have been looking at some of the personalization features in web-portals for scientific digital libraries and specialized search engines. It seems to me that personalization has not yet penetrated very deeply in scientific libraries but that this likely to change.

There are many portals that offer user-specific experiences and allow users to store queries, subscribe to e-mail alerts and customize some aspects of the portal experience. But the large portals owned by commercial science publishers (such as Web of Science, Scirus, BlackwellSynergy or ACM portal) and even open access publishers (like BioMed Central or Public Library of Science) are quite a bit less experimental than some of the specialized search engines.

I find it rather odd that Google, with it’s personal portal (different hybrid collaborative filtering / personalized search portals are also offered by Collarity and others as well) stands out as a believer in the personalized web experience. Google will keep track of your queries, display statistics about your search behaviour and offer recommendations for pages/ videos / gadgets based on your search history. Yet the quality of Google’s recommendations is necessarily limited because of the diversity of queries and interests that any individual might make in an all-purpose portal.

Scientific libraries, on the other hand, are a much better environment for personalization because the user’s interests and queries are so much more focused than in a commodity search engine. So they should be more successful at providing quality recommendations – assuming the data-sparsity problem can be overcome, which I think it can.

One encouraging observation is that some of the more specialized scientific library portals such as the International Journal of Physics show that the application of commercial clustering technology (see Clusty by Vivisimo) can really help in the query refinement process. Consumer oriented medical search engines like Medstory also return search results in clusters but with bar-charted relevance feedback within the clusters. Once the clusters are no longer restricted to pay-per-view Wall Street Journal articles (maybe Microsoft will just buy out the WSJ :-)), people will see how useful this is.

I am convinced that good recommender services are next on the agenda for progressive science libraries.

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