We present a method of searching text collections that takes advantage of the inherent hierarchrical information within documents and integrates searches of structured and unstructured data. Multidimensional databases (MDB), designed for accessing data along hierarchical dimensions, are effective for information retrieval. MDB are frequently used for On-line Analytic Processing (OLAP) applications with great success. We demonstrate a method of using OLAP techniques on a text collection. This combines traditional information retrieval and the slicing, dicing, drill-down, and roll-up of OLAP. We demonstrate use of a prototype for searching documents from the TREC collection. 1 Introduction # We propose a technique for searching text and structured data using an On-line Analytic Processing (OLAP) tool. We present how text is modeled and accessed in a multi-dimensional database, taking advantage of hierarchical information in both structured data and text. Hierarchies perme...

This paper presents an original informationretrieval engine, called MIRE, for integrating structured data and text. Among other things, MIRE is designed to work in a natural and efficient way with the inherent hierarchies of structured data. While multi-dimensional access methods have originally been developed for spatial applications, they can be successfully used to index hierarchical structured data and add to an existing information-retrieval engine the capability of navigating hierarchical dimensions. To support this capability, MIRE enhances the processing algorithms of an existing multidimensional access method to avoid overflow and support for hierarchical dimensions. Compared to a search engine with multiple indexes for a different type of search, the multidimensional approach shows a significant reduction in the number of page accesses over a large document collection.