hchen @ sims.berkeley.edu We developed a user interface that organizes Web search results into hierarchical categories. Text classification algorithms were used to automatically classify arbitrary search results into an existing category structure on-the-fly. A user study compared our new category interface with the typical ranked list interface of search results. The study showed that the category interface is superior both in objective and subjective measures. Subjects liked the category interface much better than the list interface, and they were 50 % faster at finding information that was organized into categories. Organizing search results allows users to focus on items in categories of interest rather than having to browse through all the results sequentially.

Our central claim is that user interactions with productivity applications (e.g., word processors, Web browsers, etc.) provide rich contextual information that can be leveraged to support just-in-time access to task-relevant information. As evidence for our claim, we present Watson, a system which gathers contextual information in the form of the text of the document the user is manipulating, in order to proactively retrieve documents from distributed information repositories related to task at hand, as well as process explicit requests in the context of this task. We close by describing the results of several experiments with Watson, which show it consistently provides useful information to its users. The experiments also suggest that, contrary to the assumptions of many system designers, similar documents are not necessarily useful documents in the context of a particular task. Keywords: information access; agents; context; proactive systems; automated resource discovery; similarity 1