[SOLVED] Help getting started - XLS dataset. New to Text Mining and Rapid
leonardz
New Altair Community Member
Hello,
I'm on day one in my search for a text mining tool. I came across Rapid in my Google research and my first impression is that it is one of the more robust and newbie friendly offerings.
Looking for help from the community on getting fast tracked to my first set of results using the software.
Here's the dataset I'm working with and the results I'm looking for:
1. CSV:
Software Version, Defect Description
1.0, Blah
2.0, Blah Blah Blah
3.0, Blah Blah
2.0, Blah
1.0, Blah
3.0, Blah
etc....
2. Desired Output/Analysis:
Ultimately, for each Software Version, I'm trying to identify which functions/features are the most problematic. Since the "Defect Descriptions" are not standardized and are filled in by different users, I'm hoping Rapid can help discern the most common words and phrases in "Defect Descriptions" for each Software Version.
Thanks in advance for any help you can provide.
I'm on day one in my search for a text mining tool. I came across Rapid in my Google research and my first impression is that it is one of the more robust and newbie friendly offerings.
Looking for help from the community on getting fast tracked to my first set of results using the software.
Here's the dataset I'm working with and the results I'm looking for:
1. CSV:
Software Version, Defect Description
1.0, Blah
2.0, Blah Blah Blah
3.0, Blah Blah
2.0, Blah
1.0, Blah
3.0, Blah
etc....
2. Desired Output/Analysis:
Ultimately, for each Software Version, I'm trying to identify which functions/features are the most problematic. Since the "Defect Descriptions" are not standardized and are filled in by different users, I'm hoping Rapid can help discern the most common words and phrases in "Defect Descriptions" for each Software Version.
Thanks in advance for any help you can provide.
Tagged:
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Answers
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I think I have this figured. I followed Vancouver Data's tutorial on Rapid text processing:
http://www.youtube.com/watch?v=EjD2M4r4mBM&;feature=related
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