Topic: [ANN][ICO] 🔥🔥🔥 Knoks 🔥🔥🔥 A Dedicated Platform For Crypto Signals - page 6. (Read 700 times)

I will call the person who shares the signal an Oracle

The first idea that comes to mind is... what if... you add a third parameter, that measured the rate on which an Oracle receives ratings, that is basically hidden. We decrease the scale of the original example. This would work something like this:

The platform has 100 users when the Oracle joins. And after the first signal is provided by the Oracle, if 10 more people join the network, and those 10 new people give the Oracle, a 5 star rating on it's first signal, the system keep that Oracle in a database dedicated for red-flagged Oracles.

Obviously, this can't be implemented when the platform has only 20-30 users for obvious reasons.

The database keeps in store a total of, lets say, 3 red-flags. After the 3rd red flag, it's obviously an issue. This way, even if it's a pure coincidence that the first 5 people who joined immediately after the Oracle, this can't happened 3 times in a row.

Obviously, this implies a very strict emphasis on statistics, so the system doesn't automatically activate at any scale (especially in the beginning).

Again, the red flag database should be hidden, because the scammer should not know he is being watched... that would make him bail before he faces the consequences.

you bring some very good concerns about ranking and reputation. We had the same questions in mind when we designed these into Knoks platform. We try to look at ranking and reputation as two parameters and how they should affect the signal provider and their signals. One defines the min and max price for signal in a certain group (rank) while the other can affect where within that rank the price will be.

I have to admit the solution for point 2 is ingenious. On the point 3 tho...

I guess the "statistical objective data" is represented by a set of automated rules (probably based on mathematics). Fair enough if so.

But:


I will keep on the same example with 1000 payed 5 star ratings. My concern is that someone who tries to cheat the systems aren't in it for the long run. I obviously didn't see how the platform performs and I can't know how many users will be on it, but considering this 1000 fake ratings, even if the platform gets a medium level of adoption (on which basically the competition is on a bigger scale) a 1000 5 star reviews gives the cheater an edge in power, which can be used until the system...demotes him (not to mention the huge impact it would have in a small scale adoption).

The solution implies a very big adoption as I understand, which is quite hard this days. Any solution to combat those who cheat in the early days of the project?

Hi there and thank you for the questions. I'll answer them below:
1. WP link works

2. system to avoid p&d - yes. Currently we have 2 main measurements in place. The first one is a simple threshold for minimum daily volume.
While we recognize that this one is merely enough, we have designed our smart feedback mechanism. At the end of the signal, users will be able to rate the profitability of the trade they made based on the signal recommendations.
In case of P&D, we will recognize very fast that the signal was successful (that is touching the exit price within the duration stated) but high percentage of users indicated that they made less than stated in the signal or even lost money. That type of outcome can be easily recognized by Knoks and the signal provider flagged. If needed these signal providers can be blocked. For them it will make little sense to take that approach sense it took them a while to build their ranking and reputation. It would take several months for a good signal provider to reach higher rank (there are minimum published signals and success rate thresholds). After reaching higher rank it would make no sense to said signal provider to pump some random coin because then all their progress will be lost.

3. Our ranking system is transparent and everyone will be able to verify the ranks on the ethereum blockchain. There is a direct connection between the rank and the price of a signal. Keep in mind that users review is not the only parameter that affects the rank and the price of the signal. Another part is statistical objective data like success rate.
Our rate system is just like every other peers review system - it is based on the wisdom of the crowd. One can convince or pay 1000 users to rate him 5 stars, but over time these 1000 fake reviews will be weeded out by the masses.

4. Sure. Join our telegram and PM some of the admins for more details

the WP link is working
thanks for the feedback and dont forget to signup to our beta program

1. The whitepaper doesnt work from the link on the forum

2. Do you have any systems in place to avoid pump and dumps?

3. How is the system protecting the consumers from fake ratings... For example, let's say a guy convinces 1000 people to rate him with 5 starts and then starts to pump some random coin...

4. Are you interested in a Romanian translation? (I will send you my portofolio if it's the case).

When i click on your whitepaper link, it can't open, the link is broken, so that you just know.
Good luck with your project, it is an nice idea and helping tool. 

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