Opinary has one mission: We make opinions matter. On the web and in real life. Globally, people use our polling technology to share their opinion with one simple click. The instant visualization of opinion trends enables our users to engage in an open dialogue and to understand complex debates.
By harnessing latest advances in Machine Learning, NLP and distributed systems design, our platform ensures that our content always stays relevant to the reader.
With over 80 Million monthly users, we’re one of the fastest growing startups in the media space. You’ve probably used our tools yourself on publishers like The Times, Spiegel Online, NBC, Huffington Post or the Independent.
We are looking for a Backend Engineer to support our growing product team. Our stack is primarily Go + Python, running a on top of Google Cloud Platform infrastructure.
Thanks for this! I was not aware of existing tools nor techniques to approach this problem.
I just tried to process the bender.original.png, and the result is not very good (img2xterm and util-say do a fantastic job with the same input). I will look into the half-block trick, and see if termbox-go supports something along those lines.
Keywords support is currently quite naive. This filter definitely needs to be more sophisticated. While writing the feature I just wanted to make it as simple as possible, covering the vast majority of cases with a very straightforward policy (no punctuation marks, no symbols, spaces, etc). I agree this limitation needs to be improved.
Author here. Many thanks for the positive feedback!
Apparently the most requested feature is to lower the minimum score threshold. This restriction made more sense when the keywords filter was not available: A subscription with a score threshold of less than, say, 200 points (this number was fairly arbitrary), ended up in the user being literally spammed by the service -- While testing the service, I roughly estimated that a score of 100 points is equivalent to ~1.5 emails every 15 minutes. The usability, cost, and scalability of this approach is probably not ideal.
However, now that custom keywords are involved in the criteria, I do feel like the minimum score can be lowered. Perhaps even removed, if the user has selected 1+ keywords (they are optional). I'll follow up on this feature in the GitHub issue, https://github.com/ichinaski/hnnotifications/issues/2
Thanks! The keywords are searched in the story title. The current (somewhat naive) approach simply splits the title by non letter/number characters, essentially getting rid of punctuation chars, symbols, etc
I see. Trying to detect keywords in an article could be nice improvement.
Another question, why did you limit the lower bound for the score w/ 200 ?
I assume you start indexing the HN submissions. In the long run you can create a context aware version of HN, e.g. 'Bring HN submissions with keyword X submitted during the last week.' This could be a brand new way to browse HN.
Opinary has one mission: We make opinions matter. On the web and in real life. Globally, people use our polling technology to share their opinion with one simple click. The instant visualization of opinion trends enables our users to engage in an open dialogue and to understand complex debates.
By harnessing latest advances in Machine Learning, NLP and distributed systems design, our platform ensures that our content always stays relevant to the reader.
With over 80 Million monthly users, we’re one of the fastest growing startups in the media space. You’ve probably used our tools yourself on publishers like The Times, Spiegel Online, NBC, Huffington Post or the Independent.
We are looking for a Backend Engineer to support our growing product team. Our stack is primarily Go + Python, running a on top of Google Cloud Platform infrastructure.
You can apply online here: https://opinary-gmbh.breezy.hr/p/7ff43a7eb495-backend-engine...