jekyll-feed VS hnrss

XML feeds are often generated by templating, rather than actual XML serialisation. The official Jekyll Feed plugin has this: https://github.com/jekyll/jekyll-feed/blob/master/lib/jekyll...

JSON is much more easily generated by a valid generator, and less likely to face serialisation issues.

Awesome. I was able to get this going easily enough on my jekyll-created site that uses the jekyll-feeds plugin. You just have to name the template right and it just works.

https://github.com/jekyll/jekyll-feed/#custom-styling

Disable Jekyll-feed plugin from _config.yml

It looks like this [1] plugin [2] is supported in jekyll / GitHub pages [3].

So, it seems like adding RSS / Atom feeds on a jekyll or GitHub pages site is pretty straightforward.

1. https://github.com/jekyll/jekyll-feed

2. https://docs.github.com/en/pages/setting-up-a-github-pages-s...

3. https://pages.github.com/versions/

Nice site! Another fellow note-taker inspired by Gilles Castel I see ;) Would you be willing to add an RSS feed to your site so people can follow it and get updates? It's been a while since I used jekyll but I think you just need to add jekyll-feed to the Gemfile and config.yml. See here

There is again an easy way out with the jekyll-feed plugin. Add the plugin, do a bundle install and the feed should start appearing at /feed.xml.

I was afraid of that. I was starting to think that how my Atom feed is created is not properly formed XML. I'm using this to build the feed, https://github.com/jekyll/jekyll-feed/blob/master/lib/jekyll-feed/feed.xml. See line number 66 for the content I'm talking about ({{ post.content | strip | xml_escape }}). Maybe I just can't do what I'm trying to accomplish using only XSLT. I just wanted to have the option for the user of having the summary or the full on content with HTML markup and all. BTW, the file I referenced is written with Liquid Template Language.

I have tried using the provided theme like Minima but, I just don’t like it after all. That’s why I think it’s better to create my own. I tried to create the simplest design as long as it is easy to be read. I used Coolors, Google Font, Rogue, Jekyll Paginate, Jekyll Feed, and write a bit of Ruby, CSS, and JS for creating the theme itself. I didn’t think creating this simple blog costs me 2 Saturdays, even though it only consists of as many as 3 pages.

That’s interesting.

I have predictive models that can predict if a headline (w/o the rest of the article and not considering the URL) will (a) get more than 10 votes and (b) if it does get more than 10 votes will the votes/comments ratio be more than 2 (which is roughly average)

The first model gets a ROC-AUC (see https://scikit-learn.org/stable/modules/generated/sklearn.me...) in the low 60’s (not good, the second model gets in the low 70’s (actually pretty good though it is a heat seeking missile for clickbait headlines) and my latest content-based recommender for RSS items gets almost 80. (I saw a paper that one system at TikTok gets about 85)

To do all that you need about 10,000 headlines and don’t get a lot of benefit from having more than 100,000. The ceilings on performance have more to do with the nature of the problem rather than my models: the same article can get submitted twice and get 0 votes one time and 200 the other time so it can never be as accurate as “is this an article about galactic astronomy?”

I had it ingest the HN comments firehose and found the amount of articles was overwhelming, my YOShInOn RSS reader now ingests the “best comments” from

https://hnrss.github.io/

together with 110 other feeds and actually I like the comments it picks out a lot. Now that the system is adding about 3000 items per day it might be able to handle a big feed like the comments firehose since now those comments are diluted with so many quality articles. For a problem like that you might want a two-score system with: (i) is it relevant? (something I like) and (ii) is it popular? (like Google’s PageRank)

I think you could make a model that compares comments in the best comments feed with other comments. I have tried formulating the problems above as regression problems where I try to predict the actual score and it does not work well because of the uncertainty problem but formulated as a classification problem for a score over a threshold it is easy to make a well-calibrated model that tells you “this article has a 20% chance of frontpaging” which is about the best anyone can do.

Subscribe via rss, so you can scratch the curiosity itch and each the FOMO, without coming to the site all the time and looking over the same things 20 times?

https://hnrss.github.io/

https://news.ycombinator.com/item?id=9491978

and this https://hnrss.github.io/

ps i’m ok with some % of false positives, but hopefully a sprinkle of OpenAI could keep that magically low?

thanks

It sounds interesting but I use https://hnrss.github.io/

Unless it had most of the features of hnrss.org I would not be able to use it.

Perhaps you could pivot your approach and submit a PR to hnrss for the feature?

Looks like there's an unmerged PR on the third-party hnrss project that would add this: https://github.com/hnrss/hnrss/pull/84

Check out below link to get a more customized, topic wise rss feeds.

https://hnrss.github.io/