An Integration Methodology for Autonomous Taxonomy Databases Using Priorities

In order to integrate autonomous taxonomy databases in the presence of semantic heterogeneity . we developed and evaluated a new integration algorithm over international computer networks. Whole taxonoms databases in the real applications are encoded in the relational model. First, the algorithm requires users to assign priority according to order of belief for each one of the accessible taxonom? databases. Integration is achieved by increasing the kernel database. selected by the algorithm as the one with. the high.est priority among the databases. Complex problems are included to recognize consistent parts that can be incrementally added to the kernel database in the remainder of the accessible taxonomy databases through the use of tree structures. The crZgorir/tm wirh relational operators, was proposed after considering both structural and cooperative constraints useful in managing single and multiple databases. In addition, we present a taxonomy database system including the useful algorithm. The system is also accessible from remote users through WWW (World-Wide Web) and is implemented in SQL programming and CGI (Common Gateway Inter-j&e) scripts of WWW.