Conceptual graphs as schemas for semi-structured databases

As the World Wide Web grows dramatically in recent years, there is increasing interest in semi-structured data on the web. Semi-structured data are usually represented in graph format, many graph schemas have then been proposed to extract schemas from those data graphs. Conceptual graphs, which use incremental conceptual clustering method to extract schemas, have initially been proposed in 2000. In this paper, we revise the original algorithm to generate a conceptual graph by proposing some new operators in the construction process. The results have shown that with the revised algorithm the quality of the conceptual graphs has been improved in terms of query optimization.