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RecSys Multi-Stack Ensemble for Job Recommendation, Pumpkin-Pie

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RecSys Multi-Stack Ensemble for Job Recommendation, Pumpkin-Pie

  1. 1. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Team Pumpkin-Pie T. Carpi M. Edemanti E. Kamberoski E. Sacchi R. Pagano P. Cremonesi M. Quadrana
  2. 2. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Outline • Collaborative Filtering • Content-Based • Interactions and Impressions • Multi-Stack Ensemble • Linear Ensemble • Evaluation Score Ensemble • Conclusions
  3. 3. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Collaborative-Filtering IDF value as a rate for the job
  4. 4. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Collaborative-Filtering User-based
  5. 5. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Collaborative-Filtering Item-based
  6. 6. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Content-Based Concept-based IDF value as a weight for the tag
  7. 7. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Content-Based Concept-based joint User-Item similarity
  8. 8. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Interactions & Impressions Click ReplyBookmark Already clicked jobs are likely to be clicked again
  9. 9. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Interactions & Impressions A B C D E F B C DA B D AC Dataset Filtering-step Reordering-step
  10. 10. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Multi-Stack Ensemble Past Interactions Ens CF Past Impressions UBCF 
 IntInt UBCF IntImp UBCF ImpImp UBCF ImpInt IBCF 
 IntInt IBCF ImpImp CBJUIS CBIS Baseline Ens 
 CF+CB Ens CB Final Ensemble
  11. 11. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Multi-Stack Ensemble Ens CF UBCF 
 IntInt UBCF IntImp UBCF ImpImp UBCF ImpInt IBCF 
 IntInt IBCF ImpImp CBJUIS CBIS Ens CB Stack Level 1
  12. 12. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Multi-Stack Ensemble Ens CF UBCF 
 IntInt UBCF IntImp UBCF ImpImp UBCF ImpInt IBCF 
 IntInt IBCF ImpImp CBJUIS CBIS Ens 
 CF+CB Ens CB Stack Level 2
  13. 13. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Multi-Stack Ensemble Past Interactions Ens CF Past Impressions UBCF 
 IntInt UBCF IntImp UBCF ImpImp UBCF ImpInt IBCF 
 IntInt IBCF ImpImp CBJUIS CBIS Baseline Ens 
 CF+CB Ens CB Final Ensemble Stack Level 3
  14. 14. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Linear Ensemble weight for algorithm a rank of item i in algorithm a decay for algorithm a
  15. 15. Politecnico di Milano Team Pumpkin-Pie09-15-2016 red 1.9990 pink 1.9980 yellow 1.9970 blue 1.9960 green 1.9985 orange 1.9970 purple 1.9955 red 1.9940 Algorithm A Weight 2 Decay 0.001 Algorithm B Weight 2 Decay 0.0015 Linear Ensemble 1 2 3 4 1 2 3 4
  16. 16. Politecnico di Milano Team Pumpkin-Pie09-15-2016 pink 1.9980 yellow 1.9970 blue 1.9960 green 1.9985 orange 1.9970 purple 1.9955 Algorithm A Weight 2 Decay 0.001 Algorithm B Weight 2 Decay 0.0015 Linear Ensemble red 3.9930
  17. 17. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Linear Ensemble Past Interactions Ens CF Past Impressions UBCF 
 IntInt UBCF IntImp UBCF ImpImp UBCF ImpInt IBCF 
 IntInt IBCF ImpImp CBJUIS CBIS Baseline Ens 
 CF+CB Ens CB Final Ensemble
  18. 18. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Evaluation-Score Ensemble leaderbord score # of elements
  19. 19. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Evaluation-Score Ensemble red 7.5660 pink 7.5660 purple 5.5660 orange 5.5660 yellow 9.4575 green 9.4575 blue 6.9575 grey 6.9575 Algorithm A l_a 200k n_a 1 Mln Weight 0.2 Algorithm B l_b 200k n_b 800k Weight 0.25
  20. 20. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Evaluation-Score Ensemble red 7.5660 pink 7.5660 purple 5.5660 orange 5.5660 yellow 9.4575 green 9.4575 blue 6.9575 grey 6.9575 Algorithm A l_a 200k n_a 1 Mln Weight 0.2 Algorithm B l_b 200k n_b 800k Weight 0.25
  21. 21. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Evaluation-Score Ensemble Past Interactions Ens CF Past Impressions UBCF 
 IntInt UBCF IntImp UBCF ImpImp UBCF ImpInt IBCF 
 IntInt IBCF ImpImp CBJUIS CBIS Baseline Ens 
 CF+CB Ens CB Final Ensemble
  22. 22. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Conclusions Competition promotes the algorithms that learn which are the best items among the ones recommended by the Xing platform
  23. 23. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Conclusions Multi-Stack Ensemble 4th Place Team Pumpkin-Pie

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