1 / 19

Skozi proces posodabljanja pouka matematike načrtujem učenje za danes in jutri

Skozi proces posodabljanja pouka matematike načrtujem učenje za danes in jutri. m ag. Mateja Sirnik, julij 2013. Posodobljen učni načrt za matematiko. Problemske naloge Matematično modeliranje Uporaba IKT Medpredmetno povezovanje Učenje učenja v sebinski in procesni cilji. PUN – > PRS.

brook
Download Presentation

Skozi proces posodabljanja pouka matematike načrtujem učenje za danes in jutri

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Utilizing Marginal Net Utility for Recommendation in E-commerce Author :JianWang, Yi Zhang Presented : Fen-Rou Ciou ACM, 2011

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments

  3. Motivation • To better match users’ purchase decision in the real world. • Most of existing recommendation algorithms has three disadvantages. • Marginal net utility optimization • Cannot model the above two different products well. • Highest predicted ratings to recommend.

  4. Objectives • This paper use marginal net utility to develop recommendation algorithms. • The new function contains a factor to control the product’s marginal utility diminishing rate. Marginal net utility

  5. Methodology • New marginal utility function

  6. Methodology • New marginal net utility function

  7. Methodology • Apply new marginal utility function on SVD

  8. Experiments

  9. Experiments

  10. Experiments

  11. Experiments

  12. Conclusions • On shop.com data, the new methods perform significantly better than baselines. • performs better in the re-purchase product recommendation task. • is more useful in recommending new products

  13. Comments • Advantages • . • Applications • Recommender System, Consumer Utility Function

More Related