Design of a multi-dimensional query expression for document warehouses

Abstract

During the past decade, data warehousing has been widely adopted in the business community. It provides multi-dimensional analyses on cumulated historical business data for helping contemporary administrative decision-makings. However, many data warehousing query language in present only provides on-line analytical processing (OLAP) for numeric data. For example, MDX (Multi-Dimensional eXpressions) has been proposed as a query language to allow describing multi-dimensional queries over databases with OLAP capabilities. Nevertheless, it is believed there is only about 20% information can be extracted from data warehouses concerning numeric data only, the other 80% information is hidden in non-numeric data or even in documents. Therefore, many researchers now advocate it is time to conduct research works on document warehousing to capture complete business intelligence. Document warehouses, unlike traditional document management systems, include extensive semantic information about documents, cross-document feature relations, and document grouping or clustering to provide a more accurate and more efficient access to text-oriented business intelligence. In this paper, we extend the structure of MDX into a new one containing complete constructs for querying document warehouses. The traditional MDX only contains SELECT, FROM, and WHERE clauses, which is not rich enough for document warehousing. In this paper, we present how to extend the language constructs to include GROUP BY, HAVING, and ORDER BY to design an SQL-like query language for document warehousing. The work is essential for establishing an infrastructure to help combining text processing with numeric OLAP processing technologies. Hopefully, the combination of data warehousing and document warehousing will be one of the most important kernels of knowledge management and customer relationship management applications.