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Recruit recsys-review-magambo


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review study of recsys presentation at recruit technology Japan.Presentation on the winning recsys team

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Recruit recsys-review-magambo

  1. 1. RECSYS 2016 REVIEW MAGAMBO GATETE Elie Waseda University 2016.10.29
  2. 2. Job recommendation with Hawkes processes Alibaba group ,Wenming Xiao Winner of Recsys challenge 2016 2
  3. 3. Introduction • [Recsys Challenge 2016] • • 3 PROBLEM STATEMENT Given the job role information of the users, the content of job posting, and the historical log of users activities, the key task of this contest is to recommend a list of job posts, which the users might interact with in the next week Job post | impressions | interaction | users
  4. 4. Framework • Xiao et al[2] 4 Feature Engineering Job user interact Xi Xu Bui Semantic fx Education Behavior Mat [title, industry] [0,0,1,0] [0,1] Master
  5. 5. Related work • Xiao et al[2] 5 Weak learners LR GBDT XGBOOST score 1 Score2 Score3 Pairwise scores The temporally intensity measure the interest of the user to an item in time
  6. 6. Evaluation measure 6 R: Set of predicted user item pair T: set of ground truth user item pair Pk: Precision@k
  7. 7. Review • Few feature engineering process and ensemble learning • Temporal intensity [For the recurrent user activity toward type of item, Provide intensity the user will have toward new item] • Originality: 4 • Novelty : 3 7
  8. 8. References • [2] W. Xiao, X. Xu.,K. Liang,J Mao,J Wang 2016. Job Recommendation with Hawkes Process. 10th ACM Conference on Recommender Systems - RecSys ’16 (in Press). For Recsys challenge paper and presentation slides 8