User Modeling and Recommender Systems
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Course code
IFI7128.DT
old course code
IFI7128
Course title in Estonian
Kasutaja modelleerimine ja soovitussüsteemid
Course title in English
User Modeling and Recommender Systems
ECTS credits
4.0
Assessment form
Examination
lecturer of 2023/2024 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
The course will provide the students with the conceptual knowledge enabling the design of an adaptive recommender system in various domains.
Brief description of the course
User modeling is a cross-disciplinary research field that attempts to construct models of human behavior within a specific computer environment. The goal is not to imitate human behavior but to make the machine able to understand what the expectations, goals, knowledge, information needs, and desires of a user are in terms of a specific computing environment. Recommendations utilize the information stored in a user model. Simple examples of a recommendation system are e-commerce sites which make use of the user’s pevious purchasing and browsing behavior to recommend new products or personalized news recommendation based on the user's previous news articles read.
In this class the focus is on obtaining a general understanding of state of the art user modeling techniques and recommendation mechanisms. The student will learn to critically discuss relevant topics and apply the mechanisms to different domains. They will do a course project where groups of students virtually design a system that explicitly models the user and provide recommendations in a domain chosen by the group. Students will learn about the techniques through presentations; reading/discussing seminal papers in the user modeling and recommendation literature and interactive experiments during the lecture hours. Each student will either write a survey of one chosen topic that relates to the student's interest/background or an implementation of a simple system (eg. mobile application, design prototype).
Learning outcomes in the course
Upon completing the course the student:
Students will be able to make concepts of user models and recommender systems for different application fields. Students will be able to identify an applicable configuration of algorithms/methods for a given domain.
Students are expected to acquire conceptual knowledge enabling the design of user models and recommender systems; and to develop an understanding of the limitations, drawbacks and benefits of the technologies to discuss these issues.
Teacher
Adolfo Ruiz Calleja
Additional information
Students are required to participate in 80% out of the 28 foreseen contact hours. Individual work can replace contact hours and group work (see 'Replacement Literature'). During contact hours, students are required to actively participate in discussions and interactive experiments during contact hours and in the group work.
This lecture course will be conducted in English to its design, implementation and presentation and final report, in order to be assessed.

Group work report and essay need to be handed in the latest 4 weeks after the last lecture.
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