77 citations · 158 across the 21 of their papers we have counts for
6 papers · 1 filter
ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments
Shuoqi Sun, Danula Hettiachchi, Damiano Spina
The modern information environment (MIE) is increasingly complex, shaped by a wide range of techniques designed to satisfy users' information needs. Information seeking (IS) models…
Temporal-Aware User Behaviour Simulation with Large Language Models for Recommender Systems
Xinye Wanyan, Danula Hettiachchi, Chenglong Ma +2
Large Language Models (LLMs) demonstrate human-like capabilities in language understanding, reasoning, and generation, driving interest in using LLM-based agents to simulate human…
SenseSeek Dataset: Multimodal Sensing to Study Information Seeking Behaviors
Kaixin Ji, Danula Hettiachchi, Falk Scholer +2
Information processing tasks involve complex cognitive mechanisms that are shaped by various factors, including individual goals, prior experience, and system environments. Underst…
PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation
Chenglong Ma, Ziqi Xu, Yongli Ren +2
Traditional offline evaluation methods for recommender systems struggle to capture the complexity of modern platforms due to sparse behavioural signals, noisy data, and limited mod…
Watch Out E-scooter Coming Through: Multimodal Sensing of Mixed Traffic Use and Conflicts Through Riders Ego-centric Views
Hiruni Nuwanthika Kegalle, Danula Hettiachchi, Jeffrey Chan +2
E-scooters are becoming a popular means of urban transportation. However, this increased popularity brings challenges, such as road accidents and conflicts when sharing space with…
Multi-stage Large Language Model Pipelines Can Outperform GPT-4o in Relevance Assessment
Julian A. Schnabel, Johanne R. Trippas, Falk Scholer +1
The effectiveness of search systems is evaluated using relevance labels that indicate the usefulness of documents for specific queries and users. While obtaining these relevance la…