Personalized Item Recommendations Task

A Personalized Item Recommendations Task is an item recommendations task that is a personalization task.

• Context:
  • It can be solved by a Personalized Item Recommendation System (which applies a personalized item recommendation algorithm).
  • It can range from being a Contextual Personalized Item Recommendation Task to being a Non-Contextual Personalized Item Recommendation Task.
  • It can be modeled as a Contextual Bandit Task.
  • It can (typically) be intended to achieve a higher Customer-centric KPI over non-personalized item recommendation.
  • It can range from being a Personalized Thematic-Items-Strands Recommendation Task to being an Items-in-Strand Personalized Recommendations Task.
• Example(s):
  • Personalized Movie Recommending;
  • Personalized Video Game Recommending;
  • Personalized Community Recommending;
  • Personalized Web Banner Recommending;
  • Personalized Webpage Recommendation.
  • …
• Counter-Example(s):
  • Popular Item(s) Recommending.
  • Personalized Search.
• See: Personalized Ranking, User-Item Interaction Data, Personalized Online Service, Personalized Search.

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References

2015

• https://medium.com/netflix-techblog/learning-a-personalized-homepage-aa8ec670359a
  • QUOTE: Currently, the Netflix homepage on most devices is structured with videos (movies and TV shows) organized into thematically coherent rows presented in a two-dimensional layout. Members can scroll either horizontally on a row to see more videos in that row or vertically to see other rows. Thus, a key part of our personalization approach is how we choose rows to display on the homepage. This involves figuring out how to select the rows most relevant to each member, how to populate those rows with videos, and how to arrange them on the limited page area such that selecting a video to watch is intuitive.

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