You’ve seen it before on shopping web site: you load a page displaying an item you want and see a list of other items that people bought with the one you’re viewing.
PubMed is free, but finding the important articles on a topic can cost a lot of time. To help you keep on top of the literature – with a little help from your fellow PubMed users – we are introducing a new type of link called “Articles frequently viewed together”. For some PubMed abstracts, you may see this link in the “Related Information” section in the right column.
Not all abstracts will have this link; currently, only 1.3 million out of the 24 million records in PubMed do. The calculation is based on anonymous click data for the last year, so older articles will be especially underrepresented. To find all articles with these relationships, search PubMed with the query “pubmed_pubmed_alsoviewed[filter]”. Add additional terms to narrow the focus to your area of interest.
Please give it a try and let us know what you think by adding comments to this blog post.
How does this feature work? I’m not sure I am interested in how effective this feature would be in finding relevant articles unless I understand the criteria on how you set up this link. I certainly could not explain the theory of how it works to clients who would want to understand how the articles are chosen to display to them.
Superb! Am sure it will be very useful. Do make it an easy to locate feature in the results page though!
I was wondering which clicks count for your calculations? Clicks into the abstract of an article from summary view? Clicks on the article full-text? Clicks to “Send to” an email, collection, or file?
There are a number of inputs that could be incorporated into an activity measure for PubMed records. Besides the ones you mentioned, we could also consider how much time was spent on the page or sharing to social media. We may also consider page views that follow from searches in PubMed to be more meaningful than those from other sources. Our plan is to experiment with a variety of ways to weight these inputs and then monitor their effect on usage.
I think think it is very helpful