RecSys Multi-Stack Ensemble for Job Recommendation, Pumpkin-Pie
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Slides used @ RecSys Conference 2016 by Team Pumpkin-Pie
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RecSys Multi-Stack Ensemble for Job Recommendation, Pumpkin-Pie
- 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. 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. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Collaborative-Filtering IDF value as a rate for the job
- 4. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Collaborative-Filtering User-based
- 5. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Collaborative-Filtering Item-based
- 6. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Content-Based Concept-based IDF value as a weight for the tag
- 7. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Content-Based Concept-based joint User-Item similarity
- 8. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Interactions & Impressions Click ReplyBookmark Already clicked jobs are likely to be clicked again
- 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. 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. 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. 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. 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. 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. 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. 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. 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. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Evaluation-Score Ensemble leaderbord score # of elements
- 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. 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. 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. 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. Politecnico di Milano Team Pumpkin-Pie09-15-2016 Conclusions Multi-Stack Ensemble 4th Place Team Pumpkin-Pie