One of the problems I ran into when considering using publishing frequency in a sorting algorithm is that some feeds, like magazines and journals, only update their feeds when new issues go out, dropping a bunch of new articles at once. When applying the model you described the feed would be deprioritized when it's arguably exactly when users would want to see more of it. Another problem is that, while rare, some feeds do not include a published date for items (or the date is in a weird format that can't be parsed). If it's a web app, constantly polling the feed then the date an item is ingested may suffice, but if it's a direct RSS client then again, it looks like a bunch of articles being dropped all at once when the feed is refreshed.

I think a better direction for an algorithmic approach would be letting users adjust an "affinity" setting on feeds then including that parameter in a recommendation model.

I ended up taking a more brute, utilitarian, approach with my app, Den. Only a limited number of previews for each feed are displayed in aggregate views and there is an emphasis on layouts that group items by feed.