One step in interoperating among heterogeneous databases is semantic integration: Identifying relationships between attributes or classes in dierent database schemas. SEMantic INTegrator (SEMINT) is a tool based on neural networks to assist in identifying attribute correspondences in heterogeneous databases. SEMINT supports access to a variety of database systems and utilizes both schema information and data contents to produce rules for matching corresponding attributes automatically. This paper provides theoretical background and implementation details of SEMINT. Experimental results from large and complex real databases are presented. We discuss the eectiveness of SEMINT and our experiences with attribute correspondence identi®cation in various environments. Ó

No abstract

Web performance is a key differentiation among content providers. Snafus and slowdowns at major web sites demonstrate the difficulty that companies face trying to scale to a large amount of web traffic. One solution to this problem is to store web content at server-side and edge-caches for fast delivery to the end users. However, for many e-commerce sites, web pages are created dynamically based on the current state of business processes, represented in application servers and databases . Since application servers, databases, web servers, and caches are independent components, there is no efficient mechanism to make changes in the database content reflected to the cached web pages. As a result, most application servers have to mark dynamically generated web pages as non-cacheable. In this paper, we describe the architectural framework of the CachePortal system for enabling dynamic content caching for database-driven e-commerce sites. We describe techniques for intelligently invalidating dynamically generated web pages in the caches, thereby enabling caching of web pages generated based on database contents. We use some of the most popular components in the industry to illustrate the deployment and applicability of the proposed architecture.

No abstract

No abstract