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This recollection of John Riedl, founding coeditor-in-chief of the ACM Transactions on Interactive Intelligent Systems, presents a picture by editors of the journal of what it was like to collaborate and interact with him.
Task automation systems promise to increase human productivity by assisting us with our mundane and difficult tasks. These systems often rely on people to (1) identify the tasks they want automated and (2) specify the procedural...
Characterizing and Predicting the Multifaceted Nature of Quality in Educational Web Resources
Philipp Wetzler, Steven Bethard, Heather Leary, Kirsten Butcher, Soheil Danesh Bahreini, Jin Zhao, James H. Martin, Tamara Sumner
Article No.: 15
Efficient learning from Web resources can depend on accurately assessing the quality of each resource. We present a methodology for developing computational models of quality that can assist users in assessing Web resources. The methodology...
Plan Recognition and Visualization in Exploratory Learning Environments
Ofra Amir, Ya’akov (Kobi) Gal
Article No.: 16
Modern pedagogical software is open-ended and flexible, allowing students to solve problems through exploration and trial-and-error. Such exploratory settings provide for a rich educational environment for students, but they challenge teachers to...
Recommender systems have already proved to be valuable for coping with the information overload problem in several application domains. They provide people with suggestions for items which are likely to be of interest for them; hence, a primary...
An English-Language Argumentation Interface for Explanation Generation with Markov Decision Processes in the Domain of Academic Advising
Thomas Dodson, Nicholas Mattei, Joshua T. Guerin, Judy Goldsmith
Article No.: 18
A Markov Decision Process (MDP) policy presents, for each state, an action, which preferably maximizes the expected utility accrual over time. In this article, we present a novel explanation system for MDP policies. The system interactively...
Personalized systems and recommender systems exploit implicitly and explicitly provided user information to address the needs and requirements of those using their services. User preference information, often in the form of interaction logs and...
Making Decisions about Privacy: Information Disclosure in Context-Aware Recommender Systems
Bart P. Knijnenburg, Alfred Kobsa
Article No.: 20
Recommender systems increasingly use contextual and demographical data as a basis for recommendations. Users, however, often feel uncomfortable providing such information. In a privacy-minded design of recommenders, users are free to decide for...