Elytra Blog

The simple RSS Reader. This blog publishes release notes, engineering and design details.

Improving Discoverability

Finding interesting content to read online has always been easy. Run to your nearest Subreddit Stand or Twitter Board and you’ll find yourself bombarded with a lot of information. What you wanted are topics you’re interested in. So you spend time talking to people and finding new sources. And when you do, you add its RSS Feed to your favorite Reader, like Elytra.

There is scope for improvement here. A lot of social networking services use Graphs to determine what you may want to read. That’s cool (it is, I’m completely fascinated by it) but it involves opening up your reading habits, requiring and storing your personal info, syncing your contacts so the service and find your friends and see what they are reading. It all adds to up to being a very invasive technique.

My Proposal & Implementation

I queried up the blogs in Elytra (over 9000 of them, wow!) and I was happy to see that the majority of them provide tags/categories information through the RSS Feed 1. So I decided to use this information to bring these topics of interest to you from blogs you already follow.

Tags in Unread & Blog Feeds

I’m still exploring this direction but I believe this will open up a lot of possibilities for you to discover new blogs, authors and topics of interest. This information is already made available to Elytra by the blogs and as it does not rely on your information, we successfully keep things private as usual.

I’d love to hear your thoughts on this so head over to the Reddit discussion here.

1. If you run a blog which does not expose this information through its RSS Feed, you should definitely consider adding those. ↩

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Strings, search and sanity.

Searching for content and matching it in lists in most such apps is trivially done by checking if your search input matches the title of an article or similar. This is great. It has worked for many years. However, the method naively skips out on a lot of information already available to the app. For example

  • Author’s name (when there are multiple people authoring on a website)
  • Date of publication (and matches to words like “Today”, “Yesterday” and the like)
  • Summaries

All of the above may contain information you could be searching for. Being stuck with trying to remember the name of the article you read last Sunday and finding it now is a b****. I’ve been in this position many times myself. Yes, bookmarking can save your bacon. But that method has a big single point of failure: what if you forgot to bookmark it? 

An well produced app should save you from this situation. It should save me from this situation. Depending on your current device, you may or not be able to see the tags on this post. I’ve included Levenshtein in there. If you’ve ever heard of Levenshtein distance, you’ll be familiar with how it works. If you haven’t, it’s simply a “score” of how similar or dissimilar two pieces of text are. 

Levenshtein distance is also calculated and matched against the title and summary to provide a loosely typed searching experience. So you simply need to know the “general” direction of where you’re going, and not the precise location. 

You may think this is a lot for a simple text-based search operation. It isn’t. I wonder why many haven’t already done something like this. 

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