An efficient framework for business software development
ABSTRACT Businesses operate today in an increasingly dynamic environment through a worldwide network of information exchanges and business transactions. The Semantic Web - an extension of the current Web - which comprises ontologies and XML-related technologies, provides a shared and standardized vocabulary that can be communicated among automatic and human agents to share information and knowledge. Consider that an electronic business is a set of business processes governed by business rules that run over the Internet. These business rules play a significant role in determining the success or failure of a business as a whole. The goal of this paper is to introduce a framework that is designed to build business systems faster and which can more easily accommodate changes within a business. The advantages of this framework arise from its unity and simplicity, and especially its ability to effectively change, add, and/or delete business rules.
- SourceAvailable from: pp.ua01/2000; Brooks Cole Publishing Co..
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ABSTRACT: In this paper, we present two very practical problems in the areas of distributed information retrieval and pattern mining, as well as our proposed solutions via the use of intelligent agents and domain ontologies. The first problem is to retrieve data from heterogeneous distributed data sources with a specific application to distributed Earth Science data archives. Our proposed approach is to develop an engine which acts as an interface agent by presenting users with the appearance of a single, unified, homogenous data source based on a domain ontology of Earth Science terminology. Users can then pose high-level declarative queries against this view. The system then translates each query into a set of sub-queries and spawns mobile agents to retrieve data corresponding to each sub-query. The second problem is to predict significant world events at multiple levels of abstraction by analyzing a collection of events over a period of time in order to generate sequential patterns. We specifically focus on predicting terrorist actions by analyzing terrorist group activities over time. We employ a hierarchical taxonomic organization of contextual event types to obtain higher-level abstractions of observed low-level events. With this approach, significant events can be predicted at multiple levels of abstractions with associated confidences. Although we have addressed these two problems by building prototypes in two different domains, their combination offers a powerful agent-based tool that can assist scientists and analysts by automatically retrieving and mining data collected from multiple distributed data sources. Thus with the use of relevant domain ontologies, the problems of data retrieval and pattern discovery can be combined and automated in a single, elegant system.01/2002;
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ABSTRACT: One of the core challenges for the Semantic Web is the aspect of decentralization. Local structures can be modeled by ontologies. However, in order to support global communication and knowledge exchange, mechanisms have to be developed for integrating the local systems. We adopt the database approach of autonomous federated database systems and consider an architecture for federated ontologies for the Semantic Web as starting point of our work.05/2001;