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Increasingly, business projects are ephemeral. New Business Intelligence tools must support ad-lib data sources and quick perusal. Meanwhile, tag clouds are a popular community-driven visualization technique. Hence, the authors investigate tag-cloud views with support for OLAP operations such as roll-ups, slices, dices, clustering, and drill-downs. As a case study, they implemented an application where users can upload data and immediately navigate through its ad hoc dimensions. To support social networking, views can be easily shared and embedded in other Web sites. Algorithmically, the tag-cloud views are approximate range top-k queries over spontaneous data cubes. They present experimental evidence that iceberg cuboids provide adequate online approximations. They benchmark several browser-oblivious tag-cloud layout optimizations.
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