Difference between revisions of "WinterMilestone 3 Team Enigma DarkHorseIdea: Generate tips based on accepted tasks"

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(Dark Horse idea)
 
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So we propose a solution to have a similarity index for various tasks.
 
So we propose a solution to have a similarity index for various tasks.
  
 +
* The aim here is to reduce the amount of time and effort put in by the requester to get better results from the workers
 
* Generate a similarity index for tasks from multiple submitters
 
* Generate a similarity index for tasks from multiple submitters
  
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* Eg:- A task that needs an article for product marketing. The simplest tip that could be generated is the approximate number of words expected.
 
* Eg:- A task that needs an article for product marketing. The simplest tip that could be generated is the approximate number of words expected.
  
* Other tasks from the same requester
+
----
  
 +
* The similarity index will be higher when the same requester posts similar tasks in future
 +
* A more customized form of tip can be provided for the workers when such tasks come up
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* The same model can be further utilized to '''Automatically Return''' the tasks to the users when the submission has a higher inclination to previously rejected submissions
  
  
 
[[File:7.jpg]]
 
[[File:7.jpg]]
 
  
 
== Contributors ==
 
== Contributors ==

Latest revision as of 19:18, 31 January 2016

Dark Horse idea

While each requester expects their tasks to be done in a certain way, there are widely accepted standards for different types of tasks. We observed a similar pattern in discussions on various forums. So we propose a solution to have a similarity index for various tasks.

  • The aim here is to reduce the amount of time and effort put in by the requester to get better results from the workers
  • Generate a similarity index for tasks from multiple submitters

6.jpg


  • Now based on the above similarity index, when serving a task to a worker, generate a tip or a a skeleton of the expected format of submission.
  • The tips can be based on structural or contextual pattern recognition and learning on the submissions that have already been accepted for similar tasks.
  • Naturally the algorithm should take into account the submissions that were rejected.
  • Eg:- A task that needs an article for product marketing. The simplest tip that could be generated is the approximate number of words expected.

  • The similarity index will be higher when the same requester posts similar tasks in future
  • A more customized form of tip can be provided for the workers when such tasks come up
  • The same model can be further utilized to Automatically Return the tasks to the users when the submission has a higher inclination to previously rejected submissions


7.jpg

Contributors

Archana Kumari - @dhankie

Dinesh Dhakal - @dineshd