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Token clouds for taxonomy

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ahmet furkan emrehan

A solution for taxonomy problems for overdiversified categories For Details: https://github.com/matahmet/

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Token Clouds for Taxonomy AHMET FURKAN EMREHAN matahmet@gmail.com
INTRODUCTION As time progresses, technology gets more complicated. Demands, supplies, objects and necessities get more sophisticated due to this progression. This fact over-diversifies the names or titles of these concepts. Over-diversified naming creates a taxonomy problem difficulty for handling (or managing) concepts.
MOTIVATION My approach is based on ยซnamesยป (or ยซtitlesยป in some concepts) and ยซdescriptionsยป. If we want to reduce the high number of overdiversified titles to a manageable level, we need a classification algorithm. Obviously, ยซdescriptionsยป have more information than ยซnamesยป have. I use a token set obtained from ยซdescriptionยป to reduce the number of the names.
STEP 1 First of all, for all objects we can focus two features, ยซtitlesยป (or ยซnameยป) and ยซdescriptionsยป ๐‘ก๐‘– = ๐‘ก๐‘–๐‘ก๐‘™๐‘’ (๐‘œ๐‘Ÿ ๐‘›๐‘Ž๐‘š๐‘’) ๐‘œ๐‘“ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก ๐‘– ๐‘‘๐‘– = ๐‘‘๐‘’๐‘ ๐‘๐‘Ÿ๐‘–๐‘๐‘ก๐‘–๐‘œ๐‘› ๐‘œ๐‘“ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก ๐‘– ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘– = ๐‘ ๐‘’๐‘ก ๐‘œ๐‘“ ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘  ๐‘œ๐‘๐‘ก๐‘Ž๐‘–๐‘›๐‘’๐‘‘ ๐‘“๐‘Ÿ๐‘œ๐‘š ๐‘‘๐‘– ๐‘– = 1,2,3, โ€ฆ ๐‘› ๐‘–๐‘›๐‘‘๐‘’๐‘ฅ ๐‘œ๐‘“ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก๐‘  ๐‘›; ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘กโ„Ž๐‘’ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก๐‘  ๐‘›๐‘ข; ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘ข๐‘›๐‘–๐‘ž๐‘ข๐‘’ ๐‘ก๐‘–๐‘ก๐‘™๐‘’๐‘  (๐‘œ๐‘Ÿ ๐‘›๐‘Ž๐‘š๐‘’๐‘ )
Step 2 We can define the taxonomy problem in the light of Step 1. ๐‘›๐‘ข can be very high and then is not manageable. Our goal is to create main categories to be easily managed. We can choose a number m and focus on "top m" objects and their descriptions. ๐‘— = 1,2,3, โ€ฆ ๐‘š ๐‘–๐‘›๐‘‘๐‘’๐‘ฅ ๐‘œ๐‘“ ๐‘ก๐‘–๐‘ก๐‘™๐‘’๐‘  ๐‘–๐‘› ๐‘ก๐‘œ๐‘ ๐‘š ๐‘™๐‘–๐‘ ๐‘ก ๐‘๐‘—; ๐‘š๐‘’๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘ก๐‘–๐‘ก๐‘™๐‘’ ๐‘— ๐‘–๐‘› ๐‘ก๐‘–๐‘ก๐‘™๐‘’๐‘  ๐‘œ๐‘“ ๐‘ก๐‘œ๐‘ ๐‘š ๐‘™๐‘–๐‘ ๐‘ก Now we can token clouds ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘—: = (๐‘ก๐‘–==๐‘๐‘—) ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘–
Step 3 Now we can give new taxonomy "๐‘๐‘‡" for object with i index ๐‘๐‘‡๐‘– = ๐‘๐‘—โˆ— ๐‘คโ„Ž๐‘’๐‘Ÿ๐‘’ ๐‘—โˆ— : = arg ๐‘š๐‘Ž๐‘ฅ๐‘— #(๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— โˆฉ ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘–) #(๐‘ ๐‘’๐‘ก) ๐‘–๐‘  ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘’๐‘™๐‘’๐‘š๐‘’๐‘›๐‘ก๐‘  ๐‘–๐‘› ๐‘กโ„Ž๐‘’ ๐‘ ๐‘’๐‘ก โˆ€๐‘— = 1,2,3, โ€ฆ ๐‘š, #(๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— โˆฉ ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘–)=0 then ๐‘๐‘‡๐‘– = "NA" ๐‘œ๐‘Ÿ ๐‘๐‘‡๐‘– = ๐‘ก๐‘– (๐‘–๐‘› ๐‘กโ„Ž๐‘–๐‘  ๐‘๐‘Ž๐‘ ๐‘’, ๐‘๐‘Ž๐‘ก๐‘’๐‘”๐‘œ๐‘Ÿ๐‘ฆ ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ๐‘  ๐‘œ๐‘๐‘ฃ๐‘–๐‘œ๐‘ข๐‘ ๐‘™๐‘ฆ ๐‘–๐‘›๐‘๐‘Ÿ๐‘’๐‘Ž๐‘ ๐‘’. )
Remarks 1) This model failed its initial experience. That is why some clouds tend to be very large, then the bias unavoidably occurs. To overcome this problem, emaciated clouds can be employed instead of ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— alternatively. ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— ๐‘’๐‘š : = ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— (๐‘˜โ‰ ๐‘—) ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘˜ 2) The clouds can be created by using domain knowledge if we have it. 3) Data structures of Python are suitable for the model.
The End Thanks for your attention

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Token clouds for taxonomy

  • 1. Token Clouds for Taxonomy AHMET FURKAN EMREHAN matahmet@gmail.com
  • 2. INTRODUCTION As time progresses, technology gets more complicated. Demands, supplies, objects and necessities get more sophisticated due to this progression. This fact over-diversifies the names or titles of these concepts. Over-diversified naming creates a taxonomy problem difficulty for handling (or managing) concepts.
  • 3. MOTIVATION My approach is based on ยซnamesยป (or ยซtitlesยป in some concepts) and ยซdescriptionsยป. If we want to reduce the high number of overdiversified titles to a manageable level, we need a classification algorithm. Obviously, ยซdescriptionsยป have more information than ยซnamesยป have. I use a token set obtained from ยซdescriptionยป to reduce the number of the names.
  • 4. STEP 1 First of all, for all objects we can focus two features, ยซtitlesยป (or ยซnameยป) and ยซdescriptionsยป ๐‘ก๐‘– = ๐‘ก๐‘–๐‘ก๐‘™๐‘’ (๐‘œ๐‘Ÿ ๐‘›๐‘Ž๐‘š๐‘’) ๐‘œ๐‘“ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก ๐‘– ๐‘‘๐‘– = ๐‘‘๐‘’๐‘ ๐‘๐‘Ÿ๐‘–๐‘๐‘ก๐‘–๐‘œ๐‘› ๐‘œ๐‘“ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก ๐‘– ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘– = ๐‘ ๐‘’๐‘ก ๐‘œ๐‘“ ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘  ๐‘œ๐‘๐‘ก๐‘Ž๐‘–๐‘›๐‘’๐‘‘ ๐‘“๐‘Ÿ๐‘œ๐‘š ๐‘‘๐‘– ๐‘– = 1,2,3, โ€ฆ ๐‘› ๐‘–๐‘›๐‘‘๐‘’๐‘ฅ ๐‘œ๐‘“ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก๐‘  ๐‘›; ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘กโ„Ž๐‘’ ๐‘œ๐‘๐‘—๐‘’๐‘๐‘ก๐‘  ๐‘›๐‘ข; ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘ข๐‘›๐‘–๐‘ž๐‘ข๐‘’ ๐‘ก๐‘–๐‘ก๐‘™๐‘’๐‘  (๐‘œ๐‘Ÿ ๐‘›๐‘Ž๐‘š๐‘’๐‘ )
  • 5. Step 2 We can define the taxonomy problem in the light of Step 1. ๐‘›๐‘ข can be very high and then is not manageable. Our goal is to create main categories to be easily managed. We can choose a number m and focus on "top m" objects and their descriptions. ๐‘— = 1,2,3, โ€ฆ ๐‘š ๐‘–๐‘›๐‘‘๐‘’๐‘ฅ ๐‘œ๐‘“ ๐‘ก๐‘–๐‘ก๐‘™๐‘’๐‘  ๐‘–๐‘› ๐‘ก๐‘œ๐‘ ๐‘š ๐‘™๐‘–๐‘ ๐‘ก ๐‘๐‘—; ๐‘š๐‘’๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘ก๐‘–๐‘ก๐‘™๐‘’ ๐‘— ๐‘–๐‘› ๐‘ก๐‘–๐‘ก๐‘™๐‘’๐‘  ๐‘œ๐‘“ ๐‘ก๐‘œ๐‘ ๐‘š ๐‘™๐‘–๐‘ ๐‘ก Now we can token clouds ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘—: = (๐‘ก๐‘–==๐‘๐‘—) ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘–
  • 6. Step 3 Now we can give new taxonomy "๐‘๐‘‡" for object with i index ๐‘๐‘‡๐‘– = ๐‘๐‘—โˆ— ๐‘คโ„Ž๐‘’๐‘Ÿ๐‘’ ๐‘—โˆ— : = arg ๐‘š๐‘Ž๐‘ฅ๐‘— #(๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— โˆฉ ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘–) #(๐‘ ๐‘’๐‘ก) ๐‘–๐‘  ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ ๐‘œ๐‘“ ๐‘’๐‘™๐‘’๐‘š๐‘’๐‘›๐‘ก๐‘  ๐‘–๐‘› ๐‘กโ„Ž๐‘’ ๐‘ ๐‘’๐‘ก โˆ€๐‘— = 1,2,3, โ€ฆ ๐‘š, #(๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— โˆฉ ๐‘ก๐‘œ๐‘˜๐‘’๐‘›๐‘–)=0 then ๐‘๐‘‡๐‘– = "NA" ๐‘œ๐‘Ÿ ๐‘๐‘‡๐‘– = ๐‘ก๐‘– (๐‘–๐‘› ๐‘กโ„Ž๐‘–๐‘  ๐‘๐‘Ž๐‘ ๐‘’, ๐‘๐‘Ž๐‘ก๐‘’๐‘”๐‘œ๐‘Ÿ๐‘ฆ ๐‘›๐‘ข๐‘š๐‘๐‘’๐‘Ÿ๐‘  ๐‘œ๐‘๐‘ฃ๐‘–๐‘œ๐‘ข๐‘ ๐‘™๐‘ฆ ๐‘–๐‘›๐‘๐‘Ÿ๐‘’๐‘Ž๐‘ ๐‘’. )
  • 7. Remarks 1) This model failed its initial experience. That is why some clouds tend to be very large, then the bias unavoidably occurs. To overcome this problem, emaciated clouds can be employed instead of ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— alternatively. ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— ๐‘’๐‘š : = ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘— (๐‘˜โ‰ ๐‘—) ๐‘๐‘™๐‘œ๐‘ข๐‘‘๐‘˜ 2) The clouds can be created by using domain knowledge if we have it. 3) Data structures of Python are suitable for the model.
  • 8. The End Thanks for your attention