Answers.Body: <p>I don't think this classify as an NLP problem, there is almost no semantic analysis needed, it is more like a classification problem using categorical features. </p>
  
  <p>NLTK is surely valuable if you want to perform some text 'cleaning' or preprocessing before encoding the variables. The only NLP application that I think you could apply here is some sentiment analysis on the comments to extract extra features (like a number expressing the negativeness or positiveness of each comment). Nevertheless you might want to do that using some pre-trained models cause your dataset is pretty small. </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-03-18T06:13:26.447Z
Answers.Text: Hello Eodardo,  Thanks for your reply, I was able to do this in python using dataframe itself.  I am currently adding some more enhancements to it.  I will post the completed code sometime soon.
Answers.UserDisplayName: Mani
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-03-13T02:08:26.097Z
Answers.LastActivityDate: 2020-03-13T02:08:26.097Z
Answers.UserDisplayName: Edoardo Guerriero
Body: <p>I am newbie to NLP.
  I have a excel sheet with following columns: 
      Server_SNo, 
      Owner, 
      Hosting Dept, 
      Bus owner, 
      Applications hosted, 
      Functionality,
      comments</p>
  
  <p>a. Except the Server_SNo, other columns may or may not have data.<br>
  b. For some records there is no data except Server_SNo which is the first column.
  c. One business owner can own more than 1 Server.</p>
  
  <p>So, out of 4000 records, about 50% of data contain direct mapping for a server with owner.  Remaining 50% of data have combination of other columns (Owner, Hosting Dept, Bus owner, Applications hosted, Functionality and comments)</p>
  
  <p>Here is my problem, I need to find the owner for the given Server_Sno for 50% of data which have combination of other columns (Owner, Hosting Dept, Bus owner, Applications hosted, Functionality and comments).</p>
  
  <p>I have just started to build the code using Python and NLTK.</p>
  
  <p>Is this an NLP problem? Am I going in right direction using Python and NLTK for NLP?</p>
  
  <p>Any insights is appreciated.</p>
  
  <p>-Mani</p>
  
Tags: <machine-learning><natural-language-processing><python>
Title: Owner Search for given Server SNO
UserDisplayName: Mani
ThreadText: # Owner Search for given Server SNO
  
  (Asked by: username_0 on 2020-03-10)
  
  I am newbie to NLP.
  I have a excel sheet with following columns:
  Server\_SNo,
  Owner,
  Hosting Dept,
  Bus owner,
  Applications hosted,
  Functionality,
  comments
  
  a. Except the Server\_SNo, other columns may or may not have data.  
  b. For some records there is no data except Server\_SNo which is the first column.
  c. One business owner can own more than 1 Server.
  
  So, out of 4000 records, about 50% of data contain direct mapping for a server with owner. Remaining 50% of data have combination of other columns (Owner, Hosting Dept, Bus owner, Applications hosted, Functionality and comments)
  
  Here is my problem, I need to find the owner for the given Server\_Sno for 50% of data which have combination of other columns (Owner, Hosting Dept, Bus owner, Applications hosted, Functionality and comments).
  
  I have just started to build the code using Python and NLTK.
  
  Is this an NLP problem? Am I going in right direction using Python and NLTK for NLP?
  
  Any insights is appreciated.
  
  -Mani
  
  **Tags:** machine-learning, natural-language-processing, python
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-03-13. Score: 1
  
  I don't think this classify as an NLP problem, there is almost no semantic analysis needed, it is more like a classification problem using categorical features.
  
  NLTK is surely valuable if you want to perform some text 'cleaning' or preprocessing before encoding the variables. The only NLP application that I think you could apply here is some sentiment analysis on the comments to extract extra features (like a number expressing the negativeness or positiveness of each comment). Nevertheless you might want to do that using some pre-trained models cause your dataset is pretty small.
  
  > **Comments:**
  > **username_0**: Hello Eodardo,  Thanks for your reply, I was able to do this in python using dataframe itself.  I am currently adding some more enhancements to it.  I will post the completed code sometime soon.  
  
  ---
  
  