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@@ -102,7 +102,8 @@ generation you should look at model like XXX.
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  ### Limitations and bias
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  In this project we have faced some obstacles that we had overcome, but some of those, by the nature of the project, couldn't be 100% solved.
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- Due the fact that our dataset was build it by ourselves, there was no interaction yet between a user and the dataset, therefore we don't have realistic ratings wich made us have to generate a simulation, making the results less believable.
 
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  Also in this part of the project, we have used a database of scrappings of linkedin profiles.
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  The problem is that the profiles that linkedin shows is biased, so the profiles that appears was geographically closed, or related to the users organization and email.
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  ### Limitations and bias
104
  In this project we have faced some obstacles that we had overcome, but some of those, by the nature of the project, couldn't be 100% solved.
105
+ Due the fact that our dataset was build it by ourselves, there was no interaction yet between a user and the dataset, therefore we don't have
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+ realistic ratings which made us have to generate a simulation, making the results less believable.
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  Also in this part of the project, we have used a database of scrappings of linkedin profiles.
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  The problem is that the profiles that linkedin shows is biased, so the profiles that appears was geographically closed, or related to the users organization and email.
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