User Modeling and User-Adapted Interaction

By Peter Brusilovsky. 1994

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Citations in the corpus

Reinforcement Learning based Recommender Systems: A Survey (2021, background): “Plenty of research has been done in the ield of RSs and a plethora of survey papers have been published, including RSs [12], collaborative iltering [33, 34], hybrid methods [35], multi-media RSs [36, 37], explainable recommendation [38], and article RSs [39], to name a few.”
A Deep Framework for Cross-Domain and Cross-System Recommendations (2018, background): “Later on, the work proposed in [Winoto and Tang, 2008] un-covers the relationships of user preferences in different domains, and the work proposed in [Berkovsky et al. , 2008] imports and integrates the data collected by other systems to acquire accurate modeling of users’ interests and needs.”
What would other programmers do: suggesting solutions to error messages (2010, methodology): “Linton and Schaefer [23] instrumented a Word processor to log command usage over time; based on log data, visualizations instruct users how to more effectively use the application.”
Personalized news recommendation based on click behavior (2010, unknown): “The information filtering approach has been applied to provide personalized selection of news information in various forms such as personal news agents [1], news readers for wireless devices [2, 3] and web-based news aggregators [19].”
Current challenges and visions in music recommender systems research (2017, background): “A review of dierent hybrid and ensemble recommender systems can be found in [7, 27].”
Challenges and Solutions of Ubiquitous User Modeling (2012, methodology): “This was central to the um toolkit [43, 45], which distinguished evidence in terms of the nature of its source, for example treating stereotype-based evidence as less reliable than observations of the user’s actions, which in turn might be treated as less reliable than information the user explicitl”
Cross-Domain Recommendation: Challenges, Progress, and Prospects (2021, unknown): “…et al. , 2007] has emerged to utilise the relatively richer information, e.g., user/item information [ Chung et al. , 2007 ] , thumbs-up [ Shapira et al. , 2013 ] , tags [ Fern ´ andez-Tob ´ ıas and Cantador, 2014 ] , reviews [ Tan et al. , 2014 ] , and observed ratings [ Zhu et al. ,…”
Support of the collaborative inquiry learning process: influence of support on task and team regulation (2012, methodology): “An example of tools that support students’ collaboration process are sentence openers that structure students’ communication (e.g., Baker and Lund 1997; Soller 2004).”
Using Bayesian Networks to Manage Uncertainty in Student Modeling (2002, background): “In particular, Jameson (Jameson,1996) describes a number of systems that useDempsterShafer theory (Carberry, 1990; Bauer, 1995) and Fuzzy Logic (Katz et al., 1992).”