文章基本信息

标题：EFFICIENT REVERSE SKYLINE ALGORITHM FOR DISCOVERING TOP K-DOMINANT PRODUCTS
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作者：SHAILESH KHAPRE ; M.S. SALEEM BASHA ; A. MOHAMED ABBAS 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：80
期号：2
出版社：Journal of Theoretical and Applied
摘要：Recent boom in internet growth and the advancement in internet security have led to rapid growth in Ecommerce and related services. In this context, capturing the preferences of customers plays an important role in decisions about the design and launch of new products in the market. The science that primarily deals with the support of such decisions is the Operational Research. Since many of the research problems of Operational Research have to do with the analysis of large volumes of data, therefore there has been a keen interest in data management methods to solve these problems. In this work we develop new algorithms for two problems related to the analysis of large volumes of consumer preferences, with practical applications in market research. The first problem we consider is to find the potential buyers of a product (potential customer�s identification). We formulated this problem as a reverse query skyline and propose a new algorithm called ERS. Secondly, Practical applications often require simultaneous processing of multiple queries. To resolve this problem, we formulated a new type of query, which is referred to as a query to find the k dominant candidates (k-dominant query). Our experimental evaluation validates the efﬁciency of the proposed algorithm which outperforms BRS by a huge margin.
关键词：Skyline Algorithms; Market Analysis; Personalized Service Mining; Personalized marketing; E-Commerce.