Semantic Inference on Heterogeneous E-Marketplace Activities

An electronic marketplace (e-marketplace) is a common business information space populated with many entities of different system types. Each of them has its own context of how to process activities. This leads to heterogeneous e-marketplace activities, which are difficult to make interoperable and inferred from one entity to another. This study solves this problem by proposing a concept of separation strategy and implementing it through providing a semantic inference engine with a novel inference algorithm. The solution, called the RuleXPM approach, enables one to semantically infer a next e-marketplace activity across multiple contexts/domains. Experiments show that the cross-context/cross-domain semantic inference is achievable. This paper is an understanding of many aspects related to heterogeneous activity inference

Answering an Inquiry from Heterogeneous Contexts

In this paper we study the semantic consistency maintenance issue between heterogeneous contexts, that is, how an inquiry from an unknown user of an e-marketplace can be received and answered in a semantically consistent way by a firm that is not in the context of the user’s e-marketplace. The proposed solution uses XPM to represent semantically consistent business concepts and adopts defeasible logic to reason with XPM document-oriented business rules for inquiring and offering. We motivate the approach with a real-world apartment rental problem, and explain it in architecture of collaborative business process design and automatic service provision. Finally, we report on an implementation specification within a hybrid humanagent framework. 1