clustering

Spatial layout is frequently used for managing loosely organized information, such as desktop icons and digital ink. To help users organize this type of information efficiently, we propose an interface for manipulating spatial aggregations of objects. The aggregated objects are automatically recognized as a group, and the group structure is visualized as a two-dimensional bubble surface that surrounds the objects. Users can drag, copy, or delete a group by operating on the bubble. Furthermore, to help pick out individual objects in a dense aggregation, the system spreads the objects to avoid overlapping when requested. This paper describes the design of this interface and its implementation. We tested our technique in icon grouping and ink relocation tasks and observed improvements in user performance.

Twitter streams are on overload: active users receive hundreds of items per day, and existing interfaces force us to march through a chronologically-ordered morass to find tweets of interest. We present an approach to organizing a user's own feed into coherently clustered trending topics for more directed exploration. Our Twitter client, called Eddi, groups tweets in a user's feed into topics mentioned explicitly or implicitly, which users can then browse for items of interest. To implement this topic clustering, we have developed a novel algorithm for discovering topics in short status updates powered by linguistic syntactic transformation and callouts to a search engine. An algorithm evaluation reveals that search engine callouts outperform other approaches when they employ simple syntactic transformation and backoff strategies. Active Twitter users evaluated Eddi and found it to be a more efficient and enjoyable way to browse an overwhelming status update feed than the standard chronological interface.