What is Your Current Mindset? Categories for a satisficing exploration of mobile point-of-interest recommendations

要旨

Is recommendation the new search? Recommender systems have shortened the search for information in everyday activities such as following the news, media, and shopping. In this paper, we address the challenges of capturing the situational needs of the user and linking them to the available datasets with the concept of Mindsets. Mindsets are categories such as “I'm hungry” and “Surprise me” designed to lead the users to explicitly state their intent, control the recommended content, save time, get inspired, and gain shortcuts for a satisficing exploration of POI recommendations. In our methodology, we first compiled Mindsets with a card sorting workshop and a formative evaluation. Using the insights gathered from potential end users, we then quantified Mindsets by linking them to POI utility measures using approximated lexicographic multi-objective optimisation. Finally, we ran a summative evaluation of Mindsets and derived guidelines for designing novel categories for recommender systems.

著者
Sruthi Viswanathan
NAVER LABS Europe, Meylan, France
Behrooz Omidvar-Tehrani
NAVER LABS Europe, Meylan, France
Jean-Michel Renders
NAVER LABS Europe, Meylan, France
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3501912

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Agents in the Loop

292
5 件の発表
2022-05-04 18:00:00
2022-05-04 19:15:00