Multimed Inc. partners with TrendMD to help OJS journal readers discover the article they want to read next
What to read next? To address the challenge of helping readers find the most relevant research across an ever-growing number of articles online, we have partnered with TrendMD, the world’s leading scholarly research recommendation engine. Now our OJS clients and their readers can quickly discover article recommendations related to what they just finished reading in the moment, without another search.
With TrendMD, readers will see “We recommend…. powered by TrendMD.” The recommended articles are selected based on sophisticated algorithms applied across millions of articles served each month and based on actual reader click behavior (“people that read X, also clicked on Y”), similar to what one expects at Amazon, Netflix, and Spotify.
Readers get direct links to recommended articles from the journal they are currently reading and more article recommendations related to the topic come from the TrendMD network, which includes over 2,500 publications from world leading publishers of scholarly research and professional publications.
Collaborative filtering is a powerful way to improve recommendations, identifying this type of correlation through the analysis of anonymized click data. TrendMD makes heavy use of collaborative filtering (sometimes called “The Wisdom of Crowds”) to optimize its recommendations, ensuring that the articles shown by the TrendMD recommendation widget are those predicted to be most useful, based on the pattern of recent click data of millions of other readers who have recently read the article or research on the topic.
So, now it’s easy to decide what to read next.
Contact email@example.com to see how we can add TrendMD to your OJS platform.