Investigating the use of a multi-agent system for knowledge discovery in databases
International Journal of Hybrid Intelligent Systems - VIII Brazilian Symposium On Neural Networks
Metadata with a MISSION: using metadata to query distributed statistical meta-information systems
DCMI '03 Proceedings of the 2003 international conference on Dublin Core and metadata applications: supporting communities of discourse and practice---metadata research & applications
Aggregate table-driven querying via navigation ontologies in distributed statistical databases
BNCOD'03 Proceedings of the 20th British national conference on Databases
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The World-wide Web provides an ever-increasing source of diverse information. Agent Technology provides an intelligent and flexible mechanism for querying and integrating large amounts of statistical data that are distributed among different computing systems on varioussites on the Internet.We focus on query agents, in particular the matching and negotiation agents that are responsible for pre-integration where the matching agent decomposes the query into sub-queries, and then searches metadata to find datasets that match the query fragments. In the case of heterogeneous data, the matching agent utilises a negotiation agent to find datasets that match the query fragments, provides mappings from the data to the query,and constructs the appropriate (sub-)query rewriting rules. Such matching is done by generalising the data and testing if the (sub) query is matchable to the generalised (meta) data: we call this g-matchable; if it is then we can construct an operator stack to transform the data to match the (sub) query.Such an approach provides a capability of automating the process of executing queries on heterogeneous statistical databases that are distributed over the Internet. The novelty lies in the provision of automated methods for statistical aggregates, where the heterogeneity essentially resides in the classification schemes of categorical data, including both heterogeneity of nomenclature and heterogeneity of granularity. In addition, our solution permits queries to be specified in a goal-driven query-by-example format. Rather than impose an a priori global standard, the user can query through a unified interface where integration is done at run-time.