Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU154632" target="_blank" >RIV/00216305:26230/24:PU154632 - isvavai.cz</a>

Výsledek na webu

<a href="https://dl.acm.org/doi/abs/10.1145/3616855.3635734" target="_blank" >https://dl.acm.org/doi/abs/10.1145/3616855.3635734</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank

Popis výsledku v původním jazyce

Although carousels (also-known as multilists) have become the standard user interface for recommender systems in many domains (e-commerce, streaming services, etc.) replacing the ranked list, there are many unanswered questions and undeveloped areas when compared to the literature for ranked lists. This is due to two significant barriers: lack of public datasets and lack of eye tracking user studies of browsing behavior. Clicks, the standard feedback collected by recommender systems, are insufficient to understand the whole interaction process of a user with a recommender requiring system designers to make assumptions, especially on browsing behavior. Eye tracking provides a means to elucidate the process and test these assumptions. In this extended abstract, the PhD project is outlined, which aims to address the open research questions in carousel recommender systems by: 1) improving our understanding of users' browsing behavior with carousels, 2) formulating a new click model based on

Název v anglickém jazyce

Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank

Popis výsledku anglicky

Although carousels (also-known as multilists) have become the standard user interface for recommender systems in many domains (e-commerce, streaming services, etc.) replacing the ranked list, there are many unanswered questions and undeveloped areas when compared to the literature for ranked lists. This is due to two significant barriers: lack of public datasets and lack of eye tracking user studies of browsing behavior. Clicks, the standard feedback collected by recommender systems, are insufficient to understand the whole interaction process of a user with a recommender requiring system designers to make assumptions, especially on browsing behavior. Eye tracking provides a means to elucidate the process and test these assumptions. In this extended abstract, the PhD project is outlined, which aims to address the open research questions in carousel recommender systems by: 1) improving our understanding of users' browsing behavior with carousels, 2) formulating a new click model based on

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů