User modeling

About: User modeling is a research topic. Over the lifetime, 10701 publications have been published within this topic receiving 278012 citations.

Finding your way through the rijksmuseum with an adaptive mobile museum guide

Abstract: This paper describes a real-time routing system that implements a mobile museum tour guide for providing personalized tours tailored to the user position inside the museum and interests. The core of this tour guide originates from the CHIP (Cultural Heritage Information Personalization) Web-based tools set for personalized access to the Rijksmuseum Amsterdam collection. In a number of previous papers we presented these tools for interactive discovery of user's interests, semantic recommendations of artworks and art-related topics, and the (semi-)automatic generation of personalized museum tours. Typically, a museum visitor could wander around the museum and get attracted by artworks outside of the current tour he is following. To support a dynamic adaptation of the tour to the current user position and changing interests, we have extended the existing CHIP mobile tour guide with a routing mechanism based on the SWI-Prolog Space package. The package uses (1) the CHIP user profile containing user's preferences and current location; (2) the semantically enriched Rijksmuseum collection and (3) the coordinates of the artworks and rooms in the museum. This is a joint work between the Dutch nationally funded CHIP and Poseidon projects and the prototype demonstrator can be found at http://www.chip-project.org/spacechip.

Usability trade-offs for adaptive user interfaces: ease of use and learnability

Abstract: An analysis of context-aware user interfaces shows that adaptation mechanisms have a cost-benefit trade-off for usability. Unpredictable autonomous interface adaptations can easily reduce a system's usability. To reduce this negative effect of adaptive behaviour, we have attempted to help users building adequate mental models of such systems. A user support concept was developed and applied to a context-aware mobile device with an adaptive user interface. The approach was evaluated with users and as expected, the user support improved ease of use, but unexpectedly it reduced learnability. This shows that an increase of ease of use can be realised without actually improving the user's mental model of adaptive systems.

Adaptive Hypermedia for Education and Training

Abstract: Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, Kuhme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b).

User intention modeling for interactive image retrieval

Abstract: We propose three innovative interactive methods to let computer better understand user intention in content-based image retrieval: 1. Smart intention list induces user intention, thereby improves search results by intention-specific search schema; 2. Reference strokes interaction allows user to specify in detail about the intention by pointing out interested regions; 3. Natural user feedback easily collects data of user relevance feedbacks to boost the performance of the system. Systematic user study shows that the proposed interactive mechanism improves search efficiency, reduces user workload, and enhances user experience.

Evaluating Learning Style Personalization in Adaptive Systems: Quantitative Methods and Approaches

Abstract: It is a widely held assumption that learning style is a useful model for quantifying user characteristics for effective personalized learning. We set out to challenge this assumption by discussing the current state of the art, in relation to quantitative evaluations of such systems and also the methodologies that should be employed in such evaluations. We present two case studies that provide rigorous and quantitative evaluations of learning-style-adapted e-learning environments. We believe that the null results of both these studies indicate a limited usefulness in terms of learning styles for user modeling and suggest that alternative characteristics or techniques might provide a more beneficial experience to users.