Implementing hypertext database relationships through aggregations and exceptions

Abstract

In order to combine hypertext with database facilities, we show how to extract an effective storage structure from given instance relationships. The schema of the structure recognizes clusters and exceptions. Extracting high-level structures is useful for providing a high performance browsing environment as well as efficient physical database design, especially when handling large amounts of data. This paper focuses on a clustering method, ACE, which generates aggregations and exceptions from the original graph structure in order to capture high-level relationships. The problem of minimizing the cost function is NP-complete. We use a heuristic approach based on an extended Kernighan-Lin algorithm. We demonstrate our method on a hypertext application and on a standard random graph, compared with its analytical model. The storage reductions of input database size in main memory were 77.2% and 12.3%, respectively. It was also useful for secondary storage organization for efficient retrieval.