Applying Dynamic Causal Mining in Retailing

Authors: Yi Wang

Polibits, 37, pp. 57-64, 2008.

Abstract:  With the fast development of information technology, retailers are suffering from the excess of information. Too much information can be a problem. However, more information creates more opportunity. In retailing, information is the key issue to maximizing revenue. It is now hard to make timely or effective decisions and to the right content to the right place, at the right time and in the right form. This paper is about managing the information so that the user can gain more clear insight. It is about integrating and inventing methods and techniques. The Semantic Web will provide a foundation for such a solution. However, semantics only provide a way of mapping the content of a web to user defined annotations. Not many companies have fully utilized the power of Internet retailing due to the various technical obstacles have yet to be overcome. The existing research in e-retailing focuses only on the traditional retailing including direct and indirect retailing approaches. This paper suggests that applying association mining techniques can further improve the dealing of information overload in a web oriented retailing environment.

Keywords:  Semantic web; online retailing; data mining; formal concept; Protégé; triple store; Sparql

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