User modeling

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

Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation

Abstract: In this paper, we describe research on using eye-tracking data for on-line assessment of user meta-cognitive behavior during interaction with an environment for exploration-based learning. This work contributes to user modeling and intelligent interfaces research by extending existing research on eye-tracking in HCI to on-line capturing of high-level user mental states for real-time interaction tailoring. We first describe the empirical work we did to understand the user meta-cognitive behaviors to be modeled. We then illustrate the probabilistic user model we designed to capture these behaviors with the help of on-line information on user attention patterns derived from eye-tracking data. Next, we describe the evaluation of this model, showing that gaze-tracking data can significantly improve model performance compared to lower level, time-based evidence. Finally, we discuss work we have done on using pupil dilation information, also gathered through eye-tracking data, to further improve model accuracy.

Recommending and localizing change requests for mobile apps based on user reviews

Abstract: Researchers have proposed several approaches to extract information from user reviews useful for maintaining and evolving mobile apps. However, most of them just perform automatic classification of user reviews according to specific keywords (e.g., bugs, features). Moreover, they do not provide any support for linking user feedback to the source code components to be changed, thus requiring a manual, time-consuming, and error-prone task. In this paper, we introduce ChangeAdvisor, a novel approach that analyzes the structure, semantics, and sentiments of sentences contained in user reviews to extract useful (user) feedback from maintenance perspectives and recommend to developers changes to software artifacts. It relies on natural language processing and clustering algorithms to group user reviews around similar user needs and suggestions for change. Then, it involves textual based heuristics to determine the code artifacts that need to be maintained according to the recommended software changes. The quantitative and qualitative studies carried out on 44 683 user reviews of 10 open source mobile apps and their original developers showed a high accuracy of ChangeAdvisor in (i) clustering similar user change requests and (ii) identifying the code components impacted by the suggested changes. Moreover, the obtained results show that ChangeAdvisor is more accurate than a baseline approach for linking user feedback clusters to the source code in terms of both precision (+47%) and recall (+38%).

Collaborative visualization

Abstract: Current visualization systems are designed around a single user model, making it awkward for large research teams to collectively analyse large data sets. The paper shows how the popular data flow approach to visualization can be extended to allow multiple users to collaborate-each running their own visualization pipeline but with the opportunity to connect in data generated by a colleague, Thus collaborative visualizations are 'programmed' in exactly the same 'plug-and-play' style as is now customary for single-user mode. The paper describes a system architecture that can act as a basis for the collaborative extension of any data flow visualization system, and the ideas are demonstrated through a particular implementation in terms of IRIS Explorer.

Interaction and management of devices using gaze detection

Abstract: User gaze information, which may include a user line of sight, user point of focus, or an area that a user is not looking at, is determined from user body, head, eye and iris positioning. The user gaze information is used to select a context and interaction set for the user. The interaction sets may include grammars for a speech recognition system, movements for a gesture recognition system, physiological states for a user health parameter detection system, or other possible inputs. When a user focuses on a selected object or area, an interaction set associated with that object or area is activated and used to interpret user inputs. Interaction sets may also be selected based upon areas that a user is not viewing. Multiple devices can share gaze information so that a device does not require its own gaze detector.

The berkeley UNIX consultant project

Abstract: UC (UNIX Consultant) is an intelligent, natural language interface that allows naive users to learn about the UNIX2 operating system. UC was undertaken because the task was thought to be both a fertile domain for artificial intelligence (AI) research and a useful application of AI work in planning, reasoning, natural language processing, and knowledge representation.The current implementation of UC comprises the following components: a language analyzer, called ALANA, produces a representation of the content contained in an utterance; an inference component, called a concretion mechanism, that further refines this content; a goal analyzer, PAGAN, that hypothesizes the plans and goals under which the user is operating; an agent, called UCEgo, that decides on UC's goals and proposes plans for them; a domain planner, called KIP, that computes a plan to address the user's request; an expression mechanism, UCExpress, that determines the content to be communicated to the user, and a language production mechanism, UCGen, that expresses UC's response in English.UC also contains a component, called KNOME, that builds a model of the user's knowledge state with respect to UNIX. Another mechanism, UCTeacher, allows a user to add knowledge of both English vocabulary and facts about UNIX to UC's knowledge base. This is done by interacting with the user in natural language.All these aspects of UC make use of knowledge represented in a knowledge representation system called KODIAK. KODIAK is a relation-oriented system that is intended to have wide representational range and a clear semantics, while maintaining a cognitive appeal. All of UC's knowledge, ranging from its most general concepts to the content of a particular utterance, is represented in KODIAK.