This paper presents a context-aware mobile recommender system, codenamed Magitti. Magitti is unique in that it infers user activity from context and patterns of user behavior and, without its user having to issue a query, automatically generates recommendations for content matching. Extensive field studies of leisure time practices in an urban setting (Tokyo) motivated the idea, shaped the details of its design and provided data describing typical behavior patterns. The paper describes the fieldwork, user interface, system components and functionality, and an evaluation of the Magitti prototype.
This article presents a critique of conventional collaboration transparency systems, also called "application-sharing" systems, which provide the real-time shared use of legacy single-user applications. We find that conventional collaboration transparency systems are inefficient in their use of network resources and lack support for key groupware principles: concurrent work, relaxed WYSIWIS, and group awareness. Next, we present an alternative approach to implementing collaboration transparency that provides many features previously seen only in collaboration-aware applications. Our approach is based on a replicated architecture where selected single-user interface components are dynamically replaced by multiuser versions. The replacement occurs at run-time and is transparent to the single-user application and its developers. As an instance of this approach, we describe its incorporation into a Java-based collaboration transparency system for serializable, Swing-based Java applications, called Flexible JAMM (Java Applets Made Multiuser). To validate that the flexible collaboration transparency system is truly an improvement over conventional systems, we conducted an empirical study of collaborators performing both tightly and loosely coupled tasks using Flexible JAMM versus a representative conventional collaboration transparency system, Microsoft NetMeeting. Completion times were significantly faster in the loosely coupled task using Flexible JAMM and were not adversely affected in the tightly coupled task. Accuracy was equivalent for both systems. Participants greatly preferred Flexible JAMM.
People use their awareness of others' temporal patterns to plan work activities and communication. This paper presents algorithms for programatically detecting and modeling temporal patterns from a record of online presence data. We describe analytic and end-user visualizations of rhythmic patterns and the tradeoffs between them. We conducted a design study that explored the accuracy of the derived rhythm models compared to user perceptions, user preference among the visualization alternatives, and users' privacy preferences. We also present a prototype application based on the rhythm model that detects when a person is "away" for an extended period and predicts their return. We discuss the implications of this technology on the design of computer-mediated communication.
In this paper, we describe the architecture of the vision system for the Responsive Mirror, a novel system for retail fitting rooms that enables online social fashion comparisons in physical stores based on multi-camera perception. This vision system provides implicitly controlled real-time interaction for "self" and "social" clothing comparisons by automatically tracking user's motion as she tries on clothes. We describe the key components of the motion-tracking and clothes-recognition systems and evaluate their effectiveness against images collected during a previous user study and a dataset of images representing content from a social fashion network.
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