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軌跡データのみを用いた観光スポット遷移モデルの構築

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2018年度人工知能学会全国大会
データマイニング-データマイニング応用(4)
講演番号:2O1-04
講演日時:2018年6月6日(水)

Published in: Data & Analytics
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軌跡データのみを用いた観光スポット遷移モデルの構築

  1. 1. IIYAMA Laboratory , 1
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  7. 7. IIYAMA Lab GPS 7 i h j 0.455 0.545 0.757 0.243 0.577 0.423 GPS
  8. 8. IIYAMA Lab SNS N[1] SNS I I8SNS a8 8 [1] Crandall D., Backstrom L., Huttenlocher D., Kleinberg J.: Mapping the world’s photos,Proc, 18th international conference on World wide web, pp.761-770, ACM, 2009. S8
  9. 9. IIYAMA Lab [2]Andy Yuan Xue, Rui Zhang, Yu Zheng, Xing Xie, Jin Huang, Zhenghua Xu.: Destination prediction by sub-trajectory synthesis and privacy protection against such prediction, ICDE, pp254-256, 2013. [2] 9 [3] 1 1 [3] , , .: . : , 10(1), pp101-112, 2014.
  10. 10. IIYAMA Lab GPS 0 1
  11. 11. IIYAMA Lab A B C c1 c2 • • • Mean-Shift 1 c1 c2
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  13. 13. IIYAMA Lab 1 3 1 3 3 c2 c1
  14. 14. IIYAMA Lab 0.4 0.3 0.06 0.3 0.30.3 1 0.5 0.1 0.3 0.12 0.1 0.12 0.7 0.2 0.4 0.7 0.4 0.3 0.4 i h j 0.455 0.545 0.757 0.243 0.577 0.423 i h j a b c d 4 1
  15. 15. IIYAMA Lab 1 579 1 GPS 5 1 7.15 8823
  16. 16. IIYAMA Lab 6 354 127 39 166 42 146 188 169 185 354 1 77.1
  17. 17. IIYAMA Lab 7 1 1 GPS 1 + 1
  18. 18. IIYAMA Lab 1 8 +
  19. 19. IIYAMA Lab 1 1 9 + 9
  20. 20. IIYAMA Lab 0 2 0 +
  21. 21. IIYAMA Lab 2 1 1 1 2 +
  22. 22. IIYAMA Lab 2 2 2
  23. 23. IIYAMA Lab A 11.1% B 10.9% C 7.56% D 5.53% E 4.22% … F 0.13% … G - A B C D E F G 2 3
  24. 24. IIYAMA Lab p 4 p 77.1 p p 2 p 2 2

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