Abstract
Electronic commerce is very popular nowadays. It is a fast and convenient way to transfer information and communicate with people. E-commerce uses various web services to perform a specific task. When a particular user accessed web services, they are sequentially stored into a database that is called web service sequences. Association rules are used to correlate different web services for knowledge prediction. In this paper, we design a framework for generating maximal association rules of accessed web service sequences using soft set. Soft set uses binary values for their standard representation. This framework converts web service sequences into Boolean-valued information system using the concept of coexistence attributes in a sequence. We define the concept of maximal association rules between attribute sets. Here, maximal support and confidence are also defined using soft set. Experimental results show that the proposed soft-set-based framework provides identical rules when compared with other maximal association rules and rough-set-based rules.
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