This paper describes an experiment and its results concerning research that has been going on for a number of years in the area of anthropomorphic user interface feedback. The main aims of the research have been to examine the effectiveness and user satisfaction of anthropomorphic feedback. The results are of use to all user interface designers. Currently the work in the area of anthropomorphic...

We study in this paper how explicit user feedback can be used by a case-based reasoning system to improve the quality of its retrieval phase. More specifically, we explore how both ranking feedback and relevance feedback can be exploited to modify the weights of case features. We propose some options to cope with each type of feedback. We also evaluate, in an interactive setting, their impact o...

Traditionally, the main goal of teleoperation has been in successfully achieving a given task as if carrying out the task in the local space. An emerging and related requirement is to also match the subjective sensation or user experience of the remote environment while maintaining reasonable task performance. This concept is often called “presence” or “(experiential) telepresence,” which is in...

The rapid growth of communication technologies and the invention of set-top-box (STB) and personal digital recorder (PDR) have enabled today’s television to receive and store tremendous programs. The abundance of TV programs precipitates a need for personalization tools to help people obtain programs that they really want to watch. User preference learning plays an important role in TV program ...

Inaccurate or ambiguous expressions in queries lead to poor results in information retrieval. We assume that iterative user feedback can improve the quality of queries. To this end we developed a system for image retrieval that utilizes user feedback to refine the user’s search query. This is done by a graphical user interface that returns categories of images and requires the user to choose be...

The proliferation of interest in collaborative computer applications in the past decade has resulted in a corresponding increase in the interest in multiuser interfaces. The current research seeks to contribute to an understanding of the design of multiuser interfaces for a group ranking task, and to the process of design. User requirements were identified by observing groups perform the rankin...

Explanation and dynamic feedback given to a user during the recommendation process can influence user experience. Despite this, many real-world recommender systems separate profile updates and feedback, obfuscating the relationship between them. This paper studies the effects of what we call hypothetical recommendations. These are recommendations generated by lowcost, exploratory profile manipu...

We introduce a human-computer interaction system which collaborates with a user by providing feedback during user activities. The goal of the system is to help a user complete a high-level activity that has been represented hierarchically. While a user is performing the high-level activity, our system analyzes what sub-events a user has already completed and what sub-events are needed next in o...

The new user problem (aka user cold start) is very common in online recommender systems. Active collaborative filtering (active CF) tries to solve this problem by intelligently soliciting user feedback in order to build an initial user profile with minimal costs. Existing methods only query the user for feedback on items, while users can have preferences over items as well as certain item attri...

A large number of software architectures for interactive have been described in literature, like the Seeheim, PAC-Amodeus, and Model-View-Controller architectures. Most of these architectures are based on the traditional view of interactive software, namely the view that an interactive software system can be separated in an application part and a user interface part. The application part contai...