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Predefined Topic lists

ManarManar Member Posts: 9 Newbie
Hello everyone..
I have a question.
1- When I have predefined topic lists, which contains some words to extract the suitable topic of each Arabic documents.
Cosine similarity is considered a good solution for this problem?
or latent Dirichlet allocation (LDA) ?
Please, could you guide me to do that in rapidminer?Β 
Thanks.

Answers

  • Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,625   Unicorn
    This is an interesting question.
    @mschmitz is the resident expert on LDA (well at least he has written the operator) but I am pretty sure that is not going to help you here because I don't think you can feed the LDA algorithm a predefined set of topics.

    So I am not actually sure what the best way to accomplish this would be. I guess you could put together a wordlist with the words for each predefined cluster and then try to build a polynominal classification model but that might not give you the output you really want.Β  @mschmitz do you have another approach you would recommend here?Β Β 

    P.S.Β  I don't think the language is really an issue, it has more to do with the structure of the problem.

    Brian T.
    Lindon VenturesΒ 
    Data Science Consulting from Certified RapidMiner Experts
    Manar
  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,053  RM Data Scientist
    Hi,
    so you have a word list which contains key words. The more keywords are in a text, the more likely it should be in the topic?

    That's not LDA.

    Best,
    Martin
    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
  • ManarManar Member Posts: 9 Newbie
    Ok , thank you..Β 


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