Web 2.0 OLAP: From Data Cubes to Tag Clouds

TL;DR

This paper explores integrating OLAP operations with tag clouds for dynamic, social, web-based business intelligence, enabling quick data exploration and sharing through approximate range top-k queries and layout optimizations.

Contribution

It introduces a novel approach combining OLAP with tag clouds, supporting ad hoc data analysis and social sharing in web environments.

Findings

Iceberg cuboids provide effective online approximations.

Tag-cloud views support OLAP operations like roll-ups and drill-downs.

Benchmarking shows efficient browser-oblivious layout optimizations.

Abstract

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, we investigate tag-cloud views with support for OLAP operations such as roll-ups, slices, dices, clustering, and drill-downs. As a case study, we 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, our tag-cloud views are approximate range top-k queries over spontaneous data cubes. We present experimental evidence that iceberg cuboids provide adequate online approximations. We benchmark several browser-oblivious tag-cloud layout optimizations.