Two things will emerge from that exercise: 1. there probably is in fact a reader out there that meets it, you just haven't found it yet or 2. your requirements require solving the AI-complete problem of perfectly determining what you are interested in.
Generally I find most people slot into #2. I am not kidding. I've been listening to this complaint for about 8 years now and every time I've worked with someone, it's one of the two above, and usually #2.
A third possibility is that you are just trying to read too much, period, if even an AI-complete filter would still leave you with too much. The suck may not lie with the software, it may in the requirements.
The problem of reasonably determining what someone is interested in from what they've previously read, skimmed and skipped shouldn't be "AI complete."
It only involves matching patterns to key-words. It might not be easy and the results might not be perfect but it seems possible. Using data from friends and finding the best correlates could help too. You could use the Netflix algorithm or other magic.
I suspect that's why today's readers don't satisfy - they aren't there yet and it's easy to imagine they could be.
I agree with your claim that recommendation algorithms aren't AI complete, but for different reasons.
"It only involves matching patterns to key-words." False. Recommendation might be far trickier.
Nonetheless, if you can do recommendation perfectly, it still doesn't mean that you can solve NLP, machine vision, control (robotics), planning, or any of the other major AI tasks.
But the point is that we have many examples of recommendation systems that do work reasonably well and working reasonably well is what I suspect would satisfy most users.
Further, a reader which could learn reasonably well from passive observation would give users the base do explicit tagging and rating.
Two things will emerge from that exercise: 1. there probably is in fact a reader out there that meets it, you just haven't found it yet or 2. your requirements require solving the AI-complete problem of perfectly determining what you are interested in.
Generally I find most people slot into #2. I am not kidding. I've been listening to this complaint for about 8 years now and every time I've worked with someone, it's one of the two above, and usually #2.
A third possibility is that you are just trying to read too much, period, if even an AI-complete filter would still leave you with too much. The suck may not lie with the software, it may in the requirements.