Knowledge Based Efficient E-Business Services With Multi - Agent Based Framework Using Semantic Approach For B2c Model
For the past few years, a reasonable number of agent-based systems have been proposed for developing businessto-
customer (B2C) e-commerce activities. In specific, multi-agent-systems (MAS) appear as the most optimal solution for
implementing in growing e-commerce applications. For various B2C activities, the standard behavior model, the Consumer
Buying Behavior (CBB) model is adopted in this proposed work. In CBB, personal preferences (personal profiles) are rated
at various stages, which aid our decision making process. Case Based Reasoning (CBR) process model is integrated with
CBB, to analyze and to improve the efficiency of decision making. Semantic web (XML based) and ontology will enable
automated agents to carry out more intelligent tasks on behalf of the users and for their requirements, where, ontologies can
be seen as metadata that explicitly represent semantics of data in a machine-processable way. The proposed model combines
the semantic web, ontology and agent based web service composition along with CBB and CBR so as to reduce the time
complexity and to increase the efficiency and also to provide optimal service. Ontology is integrated in this model so as to
perform meaningful web service composition. Secure e-payments are opted under the availability of financial institutions. As
a result of this proposal, “MAFS approach for B2C” is proposed. It is implemented in JADE framework, also it is
experimented and evaluated for it performance.
Keywords - CBB, CBR, MAS, Ontology, Personal Profile, Semantic Web, User and Web Service Composition.