PV202 Laboratoř servisních systémů

Fakulta informatiky
podzim 2016
Rozsah
0/0/2. 2 kr. Doporučované ukončení: k. Jiná možná ukončení: z.
Vyučující
Ing. Leonard Walletzký, Ph.D. (přednášející)
Mgr. Jitka Kitner (cvičící)
Garance
doc. RNDr. Eva Hladká, Ph.D.
Katedra počítačových systémů a komunikací – Fakulta informatiky
Dodavatelské pracoviště: Katedra počítačových systémů a komunikací – Fakulta informatiky
Rozvrh
St 12. 10. 12:00–15:50 B517, 18:00–19:50 A218, Čt 13. 10. 12:00–15:50 B517, 18:00–19:50 A217, Pá 14. 10. 10:00–13:50 A217, 14:00–15:50 A217
Předpoklady
PB114 Datové modelovaní I &&SOUHLAS
Preconditions for this course: (1) English; (2) In the seminar, the students are expected to develop their own recommender system project. It will involve some web development, algorithm implementation and system design.
Omezení zápisu do předmětu
Předmět je nabízen i studentům mimo mateřské obory.
Předmět si smí zapsat nejvýše 20 stud.
Momentální stav registrace a zápisu: zapsáno: 0/20, pouze zareg.: 0/20, pouze zareg. s předností (mateřské obory): 0/20
Mateřské obory/plány
Cíle předmětu
Course objective: The course of Recommender System for Service Science is to present the knowledge of recommender systems in the context of Service Science. The students will learn algorithms, mathematical underpinnings and up-to-date research results in recommender systems and information retrieval. The course will also provide several real-world recommender system applications such as AMAZON recommendation and booking.com recommendation to students. The students will learn and discuss the applications according to the case studies in the context of Service Science. In the seminar, the students are expected to design and try to develop a system prototype and present their work in recommender systems.
Osnova
  • The lecturer Mouzhi Ge will explain further topics from Recommender System for Service Science, e.g. Construct a recommender for Cloud IT service:
  • Introduction to Recommender Systems
  • Collaborative filtering, Content-based and Knowledge-based recommendations
  • Explanation in recommender systems
  • Recommender System and Service Science
  • Group Recommendations
  • Evaluating recommender systems
  • Case study – personalized recommendations on the Internet
  • Recommender systems and the next-generation Web
  • Recommendations in ubiquitous environments
  • Context-aware recommender system
  • Recommender system and HCI
Výukové metody
lectures, making a quick RecSys prototype
Metody hodnocení
In the seminar, the students are expected to develop their own recommender system project. It will involve some web development, algorithm implementation and system design. The students can choose the domain they like, the domain should be related to Service Science. As the block course is short, the students should at least design the system, if some students have ever done the web development before (e.g. they don’t need time to learn how to set up a server, install an IDE).
Informace učitele
https://www.unibz.it/en/public/university/default.html
Lecturer Mouzhi Ge from University of Bozen (Bolzano, Italy): Mouzhi.Ge@unibz.it
Další komentáře
Studijní materiály
Předmět je vyučován každý semestr.
Předmět je zařazen také v obdobích jaro 2007, podzim 2007, jaro 2008, podzim 2008, jaro 2009, podzim 2009, jaro 2010, podzim 2010, jaro 2011, podzim 2011, jaro 2012, podzim 2012, jaro 2013, jaro 2015, jaro 2016, jaro 2017, podzim 2017, jaro 2018, podzim 2018, jaro 2019, podzim 2019, jaro 2020, podzim 2020, jaro 2021, podzim 2021, jaro 2022, podzim 2022, jaro 2023, podzim 2023, jaro 2024, podzim 2024, jaro 2025.