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.

No abstract

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.

People interact together in all aspects of life and, as computers have become prevalent, users seek computer support for their interactions. The WWW provides an unprecedented opportunity for users to interact with each other, and the advent of JavaThfl has created a consistent computing environment to support synchronous collaboration.We describe JAMM, a prototype Java runtime environment that supports the shared use of existing Java applets, thus leveraging the existing base of software for synchronous collaboration. Our approach is based on a replicated architecture, where each user maintains their own copy of the Java applet, and the users' input events are broadcast to each applet copy. We discuss solutions to certain key problems, such as unanticipated sharing, supporting late-joiners, and replicating input sources other than user inputs (e.g., files, sockets, and random number generators).

idespread use of the Internet is giving rise to the need for collaborative applications that link users at remote sites. Many toolkits support the development of collaboration-aware applications-those developed specifically for cooperative work by multiple users. Another approach is collaboration transparency-the collaborative use of applications originally developed for a single user. When the runtime environment supports collaboration transparency, an application programmer need not write new code to make an application collaborative. Thus, collaboration transparency leverages the existing base of singleuser applications by extending them to collaborative use.

In this paper, we describe the intelligent multi-view vision technology for the Responsive Mirror, an implicitly controlled human-computer interaction system for clothes fitting rooms that allows a shopper for real-time "self" and "social" clothes comparisons. A robust motion-tracking component is designed which automatically track user's body orientations and poses as she tries on clothes. And computer vision and machine learning techniques are employed to recognize the factors that human eyes perceive in term of clothing similarity from frontal-view outfit images. We describe the key components of the motiontracking and clothes-recognition systems and evaluate their performance by user study and experiments on a simulated clothes fitting image dataset. The approach and results presented here will benefit designers and developers of similar applications in the future.