Results 141 to 150 of about 468,663 (271)

Editorial: The light and dark sides of virtual reality

open access: yesFrontiers in Virtual Reality, 2023
Sebastian Oberdörfer   +2 more
doaj   +1 more source

Tell me more: Intent Fulfilment Framework for Enhancing User Experiences in Conversational XAI [PDF]

open access: yesarXiv
The evolution of Explainable Artificial Intelligence (XAI) has emphasised the significance of meeting diverse user needs. The approaches to identifying and addressing these needs must also advance, recognising that explanation experiences are subjective, user-centred processes that interact with users towards a better understanding of AI decision ...
arxiv  

Privacy of Dependent Users Against Statistical Matching [PDF]

open access: yesarXiv, 2018
Modern applications significantly enhance user experience by adapting to each user's individual condition and/or preferences. While this adaptation can greatly improve a user's experience or be essential for the application to work, the exposure of user data to the application presents a significant privacy threat to the users\textemdash even when the ...
arxiv  

Simulating Before Planning: Constructing Intrinsic User World Model for User-Tailored Dialogue Policy Planning [PDF]

open access: yesarXiv
Recent advancements in dialogue policy planning have emphasized optimizing system agent policies to achieve predefined goals, focusing on strategy design, trajectory acquisition, and efficient training paradigms. However, these approaches often overlook the critical role of user characteristics, which are essential in real-world scenarios like ...
arxiv  

User experience strategy

open access: yes, 2013
L'objectiu d'aquest projecte era desenvolupar una metodologia de user experience strategy per aconseguir que el client d'una pàgina web tingui una mateixa experiència tant si fa servir una plataforma com una altra, aplicant diferents tècniques de disseny centrades en l'usuari.
openaire   +1 more source

Overhead-free User-side Recommender Systems [PDF]

open access: yesarXiv
Traditionally, recommendation algorithms have been designed for service developers. But recently, a new paradigm called user-side recommender systems has been proposed. User-side recommender systems are built and used by end users, in sharp contrast to traditional provider-side recommender systems. Even if the official recommender system offered by the
arxiv  

UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems [PDF]

open access: yesarXiv
Reinforcement learning (RL) has gained traction for enhancing user long-term experiences in recommender systems by effectively exploring users' interests. However, modern recommender systems exhibit distinct user behavioral patterns among tens of millions of items, which increases the difficulty of exploration.
arxiv  

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