Towards psychology-aware preference construction in recommender systems: Overview and research issues
User preferences are a crucial input needed by recommender systems to determine relevant
items. In single-shot recommendation scenarios such as content-based filtering and …
items. In single-shot recommendation scenarios such as content-based filtering and …
Explanatory interactive machine learning
S Teso, K Kersting - Proceedings of the 2019 AAAI/ACM Conference on …, 2019 - dl.acm.org
Although interactive learning puts the user into the loop, the learner remains mostly a black
box for the user. Understanding the reasons behind predictions and queries is important …
box for the user. Understanding the reasons behind predictions and queries is important …
Preferences in artificial intelligence
The paper presents a focused survey about the presence and the use of the concept of
“preferences” in Artificial Intelligence. Preferences are a central concept for decision making …
“preferences” in Artificial Intelligence. Preferences are a central concept for decision making …
PTIME: Personalized assistance for calendaring
PM Berry, M Gervasio, B Peintner… - ACM Transactions on …, 2011 - dl.acm.org
In a world of electronic calendars, the prospect of intelligent, personalized time management
assistance seems a plausible and desirable application of AI. PTIME (Personalized Time …
assistance seems a plausible and desirable application of AI. PTIME (Personalized Time …
Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process
Two problems may arise when an intelligent (recommender) system elicits users'
preferences. First, there may be a mismatch between the quantitative preference …
preferences. First, there may be a mismatch between the quantitative preference …
User-involved preference elicitation for product search and recommender systems
We address user system interaction issues in product search and recommender systems:
how to help users select the most preferential item from a large collection of alternatives. As …
how to help users select the most preferential item from a large collection of alternatives. As …
" I Want It That Way": Enabling Interactive Decision Support Using Large Language Models and Constraint Programming
A critical factor in the success of decision support systems is the accurate modeling of user
preferences. Psychology research has demonstrated that users often develop their …
preferences. Psychology research has demonstrated that users often develop their …
Constructive preference elicitation by setwise max-margin learning
In this paper we propose an approach to preference elicitation that is suitable to large
configuration spaces beyond the reach of existing state-of-the-art approaches. Our setwise …
configuration spaces beyond the reach of existing state-of-the-art approaches. Our setwise …
[PDF][PDF] SAT solving in interactive configuration
M Janota - 2010 - sat.inesc-id.pt
Computer users encounter configuration on daily basis. Whether when they customize an
application they use, customize how a new application is installed, or just customize a query …
application they use, customize how a new application is installed, or just customize a query …
PriCal: context-adaptive privacy in ambient calendar displays
PriCal is an ambient calendar display that shows a user's schedule similar to a paper wall
calendar. PriCal provides context-adaptive privacy to users by detecting present persons …
calendar. PriCal provides context-adaptive privacy to users by detecting present persons …