AVATAR: Main Design Decisions ● Motivation of Tv A TV recommender system based on the experience gained Recommender Systems in the field of semantic Web ● Related Work e Main Design Decisions e The Architecture ● The Contributions of AVATAR ●TheL| KO language ● Conclusions ● Further Work Slide 4/14
● Motivation of TV Recommender Systems ● Related Work ● Main Design Decisions ● The Architecture ● The Contributions of AVATAR ● The LIKO language ● Conclusions ● Further Work Slide 4/14 AVATAR: Main Design Decisions (I) ■ A TV recommender system based on the experience gained in the field of Semantic Web. ■ Semantic reasoning about user preferences and TV contents. Key elements are: ◆ TV-Anytime specification for: ■ Generic descriptions of TV programs: title, genre, set of keywords, etc. ■ User preferences ■ User viewing history ◆ Knowledge about TV domain provided by an OWL ontology
AVATAR: Main Design Decisions ● Motivation of Tv A TV recommender system based on the experience gained Recommender Systems in the field of semantic Web ● Related Work e Main Design Decisions e The Architecture Semantic reasoning about user preferences and TV ● The Contributions of contents. Key elements are AVATAR ●TheL| KO language ● Conclusions ● Further Work Slide 4/14
● Motivation of TV Recommender Systems ● Related Work ● Main Design Decisions ● The Architecture ● The Contributions of AVATAR ● The LIKO language ● Conclusions ● Further Work Slide 4/14 AVATAR: Main Design Decisions (I) ■ A TV recommender system based on the experience gained in the field of Semantic Web. ■ Semantic reasoning about user preferences and TV contents. Key elements are: ◆ TV-Anytime specification for: ■ Generic descriptions of TV programs: title, genre, set of keywords, etc. ■ User preferences ■ User viewing history ◆ Knowledge about TV domain provided by an OWL ontology
AVATAR: Main Design Decisions ● Motivation of Tv A TV recommender system based on the experience gained Recommender Systems in the field of semantic Web ● Related Work e Main Design Decisions e The Architecture Semantic reasoning about user preferences and T ● The Contributions of contents. Key elements are AVATAR ●TheL| KO language TV-Anytime specification for ● Conclusions ● Further Work a Generic descriptions of TV programs: title, genre, set of keywords, etc User preferences User viewing history Knowledge about Tv domain provided by an OWL ontology Slide 4/14
● Motivation of TV Recommender Systems ● Related Work ● Main Design Decisions ● The Architecture ● The Contributions of AVATAR ● The LIKO language ● Conclusions ● Further Work Slide 4/14 AVATAR: Main Design Decisions (I) ■ A TV recommender system based on the experience gained in the field of Semantic Web. ■ Semantic reasoning about user preferences and TV contents. Key elements are: ◆ TV-Anytime specification for: ■ Generic descriptions of TV programs: title, genre, set of keywords, etc. ■ User preferences ■ User viewing history ◆ Knowledge about TV domain provided by an OWL ontology
AVATAR: Main Design Decisions(I) ● Motivation of Tv a The system must be updated when user preferences Recommender Systems ● Related Work lange e Main Design Decisions Goal: personalized and higher quality recommendations e The Architecture ● The Contributions of AVATAR ●TheL| KO language ● Conclusions ● Further Work
● Motivation of TV Recommender Systems ● Related Work ● Main Design Decisions ● The Architecture ● The Contributions of AVATAR ● The LIKO language ● Conclusions ● Further Work Slide 5/14 AVATAR: Main Design Decisions (II) ■ The system must be updated when user preferences change. ◆ Goal: personalized and higher quality recommendations. ■ AVATAR must be flexible enough to favor updating process. ◆ MHP applications tuned in user’s receiver (Set-Top Box or STB). ■ MHP applications run in the context of a service or event. ◆ Problem: All user actions must be recorded all the time: local agent to watch the viewer behaviour. ◆ Local agent stores feedback information. ◆ Normalized access by TV-Anytime MHP API