Skupinové rozhodování ve skupinových doporučovacích systémech

• Název práce v češtině: Skupinové rozhodování ve skupinových doporučovacích systémech
• Název v anglickém jazyce: Group decision making in group recommender systems
• Klíčová slova: doporučovací systémy|skupinové doporučení
• Klíčová slova anglicky: recommender systems|group recommendation
• Akademický rok vypsání: 2023/2024
• Typ práce: bakalářská práce
• Ústav: Katedra softwarového inženýrství (32-KSI)
• Vedoucí / školitel: RNDr. Patrik Dokoupil
• Řešitel: skrytý - zadáno a potvrzeno stud. odd.
• Datum přihlášení: 02.04.2024
• Datum zadání: 07.04.2024
• Datum potvrzení stud. oddělením: 08.04.2024

Zásady pro vypracování

The student should initially acquire a fundamental understanding of recommender systems (RS), group recommender systems (GRS), and the principles of group decision-making as outlined in the literature. Subsequently, the student should review the decision-making methodologies in relevant studies.

Afterward, the student is expected to design and implement a supportive tool, such as a website, that facilitates researchers in conducting user studies. These studies should focus on exploring the processes through which groups form decisions and interact with GRS. This tool should enable the creation of new user study instances that researchers can share with participants. Once participants join a study, the website must guide them throughout the entire GRS cycle, which includes preference elicitation, completing demographics/questionnaires, generating group recommendations, and making decisions within the group. Other essential features of the website include enabling communication among users and providing mechanisms to streamline the initial group recommendations into a shorter list of options.

Seznam odborné literatury

1. Ricci, F. et al (Eds): Recommender Systems Handbook, Springer, 2022

2. Felfernig, A. \& Boratto, L. \& Stettinger, M. \& Tkalčič, M. (2018). Group Recommender Systems - An Introduction.

3. Daniel Herzog and Wolfgang Wörndl. 2019. A User Study on Groups Interacting with Tourist Trip Recommender Systems in Public Spaces. In Procs. of the 27th ACM Conference on User Modeling, Adaptation and Personalization. 130–138.

4. Álvarez Márquez, J.O., Ziegler, J. (2016). Hootle+: A Group Recommender System Supporting Preference Negotiation. In: Yuizono, T., Ogata, H., Hoppe, U., Vassileva, J. (eds) Collaboration and Technology. CRIWG 2016. Lecture Notes in Computer Science(), vol 9848. Springer, Cham.

5. Nguyen, T.N., Ricci, F. A chat-based group recommender system for tourism. Inf Technol Tourism 18, 5–28 (2018).

6. David Contreras, Maria Salamó, and Ludovico Boratto. 2021. Integrating Collaboration and Leadership in Conversational Group Recommender Systems. ACM Trans. Inf. Syst. 39, 4, Article 41 (October 2021), 32 pages.

Předběžná náplň práce v anglickém jazyce

Recommender systems are tools that are ubiquitous in our everyday lives and their importance is still growing. Nowadays, most online services, for example, social networks, news services, streaming services, or news websites adopt some form of a recommendation. Since people are exposed to recommender systems on a daily basis and they are affected by their performance, fairness, and other attributes, it should be our role (as researchers) to work on improving these systems and preventing possible negative effects they may pose to the user. One of the emerging sub-domains of recommender systems is group recommender systems, where the goal is to recommend items to whole groups of people, instead of individuals, for example, recommend a movie to a group of friends to watch together. Despite the fact that group recommender systems are becoming more and more popular (and thus studied) they are still not understood well enough. Some of the questions that still don't have a clear answer are related to group decision-making in selecting a single item from the group recommendation, e.g. how does the group come to a decision? What do they consider as important? The main goal of this thesis is to design and develop a supportive tool that will help conduct user studies concerned with further investigation of these questions.