Information extraction agents for service-oriented architecture using web service systems: A framework
In some business domains, such as financial investment services, maintaining current information is a serious challenge, as markets evolve by the hour. This creates a demand for continually-updated information systems to support business decision-makers. Many sources of domain information are online documents containing unstructured text. For the information encoded in these natural language texts to be usable by systems, it must be extracted and reshaped into forms which those systems can recognize. The goal of this research is to investigate ways to exploit information-rich, online source texts in order to automatically update information in web service (WS) systems implemented in service-oriented architecture (SOA) environments. We propose a general framework for service-oriented web service systems that incorporates information extraction (IE) components capable of handling unstructured text. Since IE systems are sophisticated and difficult to implement, performance and economic considerations suggest that firms with special expertise should perform these tasks and sell the services to service customers. Our prototype information extraction system, which can be embedded in a WS system, is described to illustrate the framework.
web services (ws) service-oriented architecture (soa) information extraction (ie) natural language processing (nlp)