Enhancing the E-business Through Generalized Association Rule Mining from the Web-Based Data

Abstract

AbstractPresent market focuses on “Know your customer” and relies on advertisement and user’s navigation habits. The data collected from Internet and various Web sites is known as Web-based data, i.e., collection of Web pages. The Web pages available on Internet are in form of different levels and make multilevel taxonomy. Generalized multilevel association rule mining considers the items or predicates mined are at different levels of taxonomy. The generalized association rule mining can help to decide the plans for enhancing the business as well as it will also help to target the promotional offers and advertisement for customers with personal care. In this paper, it has been shown how generalized multilevel association rule mining is integrated to the knowledge discovery process, its potential applications, and techniques. Furthermore, an integrated approach has been presented showing how multilevel association rule mining can contribute to e-business via its great potential. Finally, generalized association rule mining algorithms have been presented for discussing the process of enhancing the e-business.KeywordsGeneralized association rule miningMultilevel taxonomyCandidate generation