Contextualizing data warehouses with documents

Current data warehouse and OLAP technologies are applied to analyze the structured data that companies store in databases. The context that helps to understand data over time is usually described separately in text-rich documents. This paper proposes to integrate the traditional corporate data warehouse with a document warehouse, resulting in a contextualized warehouse. Thus, the user first selects an analysis context by supplying some keywords. Then, the analysis is performed on a novel type of OLAP cube, called an R-cube, which is materialized by retrieving and ranking the documents and corporate facts related to the selected context.