Alan Said

Recommended for You: The Making of a RecSys Community

Alan Said, Michael D. Ekstrand, Maria Soledad Pera

A reflection on the RecSys community, aligning with the 20th anniversary of its flagship conference, ACM RecSys

se, us, nl (code pays fourni par la source)

Recommended for You: The Making of a RecSys Community

Alan Said, Michael D. Ekstrand, Maria Soledad Pera

A reflection on the RecSys community, aligning with the 20th anniversary of its flagship conference, ACM RecSys

se, us, nl (code pays fourni par la source)

Introduction to the Special Issue on Recommender Systems for Good

Marko Tkalčič, Antonela Tommasel, Noemi Mauro, Nava Tintarev et autres

In this special issue, we bring together contributions that frame recommender systems for good as a broader reorientation of recommender systems research toward societal impact, responsibility, inclusion, and beneficial intervention. The papers collected here help define the emerging RS4Good agenda, examine its …

si, at, ar, it, nl, se (code pays fourni par la source)

Recommender systems for good (RS4Good)

Dietmar Jannach, Alan Said, Marko Tkalčič, Markus Zanker

In the area of recommender systems, the vast majority of research efforts is spent on developing increasingly sophisticated recommendation models, also using increasingly more computational resources. Unfortunately, most of these research efforts target a very small set of application domains, mostly e-commerce …

at, se (code pays fourni par la source)

Reproducibility in Recommender Systems: A Survey

Alan Said, Alejandro Bellogín

Reproducibility has become a cornerstone of credible recommender systems research, driven by growing concerns about the reliability and generalizability of experimental results. In response, the ACM RecSys conference introduced a dedicated Reproducibility Track in 2020 to encourage rigorous, transparent, and repeatable research. …

se, es (code pays fourni par la source)

Reproducibility in Recommender Systems: A Survey

Alan Said, Alejandro Bellogin

Reproducibility has become a cornerstone of credible recommender systems research, driven by growing concerns about the reliability and generalizability of experimental results. In response, the ACM RecSys conference introduced a dedicated Reproducibility Track in 2020 to encourage rigorous, transparent, and repeatable research. …

Reproducibility in Recommender Systems: A Survey

Alan Said, Alejandro Bellogin

Reproducibility has become a cornerstone of credible recommender systems research, driven by growing concerns about the reliability and generalizability of experimental results. In response, the ACM RecSys conference introduced a dedicated Reproducibility Track in 2020 to encourage rigorous, transparent, and repeatable research. …

Designing Trustworthy LLM-based Wellbeing Recommendation through Controllable Interaction

Alan Said, Alexandra Weilenmann

Large language models (LLMs) are increasingly used to generate personalized guidance in wellbeing contexts such as physical activity, stress management, and mental health support, enabling fluent and context-aware interaction but relying on largely implicit mechanisms that shape how recommendations are expressed and …

Designing Trustworthy LLM-based Wellbeing Recommendation through Controllable Interaction

Alan Said, Alexandra Weilenmann

Large language models (LLMs) are increasingly used to generate personalized guidance in wellbeing contexts such as physical activity, stress management, and mental health support, enabling fluent and context-aware interaction but relying on largely implicit mechanisms that shape how recommendations are expressed and …

se (code pays fourni par la source)

Trust as a Situated User State in Social LLM-Based Chatbots

Annie Landerberg, Kari Flatmo, Alan Said

Social chatbots based on large language models are increasingly embedded in everyday platforms, yet how users develop trust in these systems over time remains unclear. We present a four-week longitudinal qualitative survey study (N = 27) of trust formation in Snapchat’s My …

se (code pays fourni par la source)

Trust as a Situated User State in Social LLM-Based Chatbots: A Longitudinal Study of Snapchat's My AI

Annie Landerberg, Kari Flatmo, Alan Said

Social chatbots based on large language models are increasingly embedded in everyday platforms, yet how users develop trust in these systems over time remains unclear. We present a four-week longitudinal qualitative survey study (N = 27) of trust formation in Snapchat's My …

Early Explorations of Recommender Systems for Physical Activity and Well-Being

Alan Said

se (code pays fourni par la source)