search

Studies of search habits reveal that people engage in many search tasks involving collaboration with others, such as travel planning, organizing social events, or working on a homework assignment. However, current Web search tools are designed for a single user, working alone. We introduce SearchTogether, a prototype that enables groups of remote users to synchronously or asynchronously collaborate when searching the Web. We describe an example usage scenario, and discuss the ways SearchTogether facilitates collaboration by supporting awareness, division of labor, and persistence. We then discuss the findings of our evaluation of SearchTogether, analyzing which aspects of its design enabled successful collaboration among study participants.

NP-hard combinatorial optimization problems are common in real life. Due to their intractability, local search algorithms are often used to solve such problems. Since these algorithms are heuristic-based, it is hard to understand how to improve or tune them. We propose an interactive visualization tool, VIZ, meant for understanding the behavior of local search. VIZ uses animation of abstract search trajectories with other visualizations which are also animated in a VCR-like fashion to graphically playback the algorithm behavior. It combines generic visualizations applicable on arbitrary algorithms with algorithm and problem specific visualizations. We use a variety of techniques such as alpha blending to reduce visual clutter and to smooth animation, highlights and shading, automatically generated index points for playback, and visual comparison of two algorithms. The use of multiple viewpoints can be an effective way of understanding search behavior and highlight algorithm behavior which might otherwise be hidden.

Studies of search habits reveal that people engage in many search tasks involving collaboration with others, such as travel planning, organizing social events, or working on a homework assignment. However, current Web search tools are designed for a single user, working alone. We introduce SearchTogether, a prototype that enables groups of remote users to synchronously or asynchronously collaborate when searching the Web. We describe an example usage scenario, and discuss the ways SearchTogether facilitates collaboration by supporting awareness, division of labor, and persistence. We then discuss the findings of our evaluation of SearchTogether, analyzing which aspects of its design enabled successful collaboration among study participants.

We present three new interaction techniques for aiding users in collecting and organizing Web content. First, we demonstrate an interface for creating associations between websites, which facilitate the automatic retrieval of related content. Second, we present an authoring interface that allows users to quickly merge content from many different websites into a uniform and personalized representation, which we call a card. Finally, we introduce a novel search paradigm that leverages the relationships in a card to direct search queries to extract relevant content from multiple Web sources and fill a new series of cards instead of just returning a list of webpage URLs. Preliminary feedback from users is positive andvalidates our design.

Spoken language interfaces provide highly mobile, small form-factor, hands-free, eyes-free interaction with information. Uniform access to large lists of information using spoken interfaces is highly desirable, but problematic due to inherent limitations of speech. A speech widget for lists of attributed objects is described that provides for approximate queries to retrieve desired items. User tests demonstrate that this is an effective technique for accessing information using speech.

Re-finding, a common Web task, is difficult when previously viewed information is modified, moved, or removed. For example, if a person finds a good result using the query "breast cancer treatments", she expects to be able to use the same query to locate the same result again. While re-finding could be supported by caching the original list, caching precludes the discovery of new information, such as, in this case, new treatment options. People often use search engines to simultaneously find and re-find information. The Re:Search Engine is designed to support both behaviors in dynamic environments like the Web by preserving only the memorable aspects of a result list. A study of result list memory shows that people forget a lot. The Re:Search Engine takes advantage of these memory lapses to include new results where old results have been forgotten.

Thumbnail images provide users of image retrieval and browsing systems with a method for quickly scanning large numbers of images. Recognizing the objects in an image is important in many retrieval tasks, but thumbnails generated by shrinking the original image often render objects illegible. We study the ability of computer vision systems to detect key components of images so that automated cropping, prior to shrinking, can render objects more recognizable. We evaluate automatic cropping techniques 1) based on a general method that detects salient portions of images, and 2) based on automatic face detection. Our user study shows that these methods result in small thumbnails that are substantially more recognizable and easier to find in the context of visual search.

We propose WindowScape, a window manager that uses a photograph metaphor for lightweight, post hoc task management. This is the first task management windowing model to provide intuitive accessibility while allowing windows to exist simultaneously in multiple tasks. WindowScape exploits users' spatial and visual memories by providing a stable thumbnail layout in which to search for windows. A function is provided to let users search the window space while maintaining a largely consistent screen image to minimize distractions. A novel keyboard interaction technique is also presented.

Studies of search habits reveal that people engage in many search tasks involving collaboration with others, such as travel planning, organizing social events, or working on a homework assignment. However, current Web search tools are designed for a single user, working alone. We introduce SearchTogether, a prototype that enables groups of remote users to synchronously or asynchronously collaborate when searching the Web. We describe an example usage scenario, and discuss the ways SearchTogether facilitates collaboration by supporting awareness, division of labor, and persistence. We then discuss the findings of our evaluation of SearchTogether, analyzing which aspects of its design enabled successful collaboration among study participants.

Programmers regularly use search as part of the development process, attempting to identify an appropriate API for a problem, seeking more information about an API, and seeking samples that show how to use an API. However, neither general-purpose search engines nor existing code search engines currently fit their needs, in large part because the information programmers need is distributed across many pages. We present Assieme, a Web search interface that effectively supports common programming search tasks by combining information from Web-accessible Java Archive (JAR) files, API documentation, and pages that include explanatory text and sample code. Assieme uses a novel approach to finding and resolving implicit references to Java packages, types, and members within sample code on the Web. In a study of programmers performing searches related to common programming tasks, we show that programmers obtain better solutions, using fewer queries, in the same amount of time spent using a general Web search interface.