The applications largely focus on using rules for e-contracting, web services, and financial knowledge integration.
SWS offers the promise of dramatically increasing the degree of automation (and lowering costs) in machine-to-machine/application-to-application communications and business processes, as compared to the first generation of the Web which is primarily oriented towards human-to-machine/human-to-application interactions.
Siglaunch not updating
The focus is especially on information about business rules or policies, including in e-contracts.
The technical approach is based on declarative logic programs.
This semantics is defined in terms of what conclusions are sanctioned from a given set of premises (e.g., rules or ontological definitions) in a particular chosen KR.
The semantic aspect of KR is important to enable an agent/application to anticipate what another agent/application will believe/draw from a given set of communicated statements (i.e., exchanged information/knowledge).
An "ontology" is a formally specified set of vocabulary definitions. Rules mention relations and other logical constants, and thus can rely on ontological definitions of those.
"Knowledge representation" (KR) means what form of knowledge can be expressed, including both syntactic encoding and underlying semantics of meaning.
Other applications included in catalogs & storefronts, security/authorization/trust, and personalization.
My research overall is concerned with the design and management of how automated enterprises and intelligent agents will soon communicate at a high level of shared understanding ("semantics") with each other over the Web in e-commerce (esp. Two important technical aspects of this are (1.) XML and (2.) techniques for knowledge representation and inferencing, especially for rules and ontologies.
This project is concerned largely with communication of rule-form beliefs (information), assimilation of such beliefs from multiple sources, reasoning about the scope and degree of trust of those sources, handling of conflicts between those sources, and inter-operable executability of inferencing with those beliefs via knowledge-based and database systems.
The sources might be agents, applications, or databases, for example.
This resulted in IBM Common Rules which pioneered rules inter-operability and conflict handling, using the technical approach based largely on declarative logic programs in Java and XML which has been continued in SWEET and Rule ML.