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Tag relations discovery

Explore the importance of tagging in organizing unstructured web content and discover how tag distribution affects categorization. Analyze tag relations discovery methods, including cooccurrence, cosine similarity, FolkRank, and tag frequency.

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Tag relations discovery

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  1. Tomas Michalek BP/IIT.SRC Tag relations discovery

  2. Tag relations discovery • Why we tag? • Tag distribution • Tag categories • Tag relations discovery systems • Which will work?

  3. Why we tag content? • Unstructured text • Most of the web content • Delicious.com • Structred text • Better automatic text processing • Better results for text mining methods • Pictures, audio, video • Very hard automatic processing, even if impossible • All information are from users • flickr.com

  4. Tag distribution • Graph tag distribution for 3 systems – flickr, delicious, citeULike • Is purpouse of tag collecting affecting it's distribution?

  5. Flickr.com

  6. Delicious.com

  7. Delicious.com • 1 - 43,83% • 1-2 - 66,08% • 1-3 - 79,03% • 1-4 - 86,3% • 1-5 - 90,53%

  8. SiteULike.com

  9. siteULike.com • 1 - 43,53 • 1-2 - 58,99 • 1-3 - 71,28% • 1-4 - 79,3% • 1-5 - 84,27% • 1-6 - 87,5% • 1-7 - 90,34%

  10. Categorization - Flickr.com

  11. Categorization - Delicious.com

  12. Relations discovery

  13. Relations discovery • Methods • Coocurrence • Cosine similarity • I found two versions • FolkRank • Tag Frequency • Based on • Tag coocurrence on resources • User history

  14. Cosine similarity

  15. Relations discovery • Methods • Coocurrence • Cosine similarity • I found two versions • FolkRank • Tag Frequency • Based on • Tag coocurrence on resources • User history

  16. http://217.67.16.40:800 • Apple

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