2011
DOI: 10.5267/j.msl.2011.06.011
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Improving electronic customers' profile in recommender systems using data mining techniques

Abstract: Recommender systems are tools for realization one to one marketing. Recommender systems are systems, which attract, retain, and develop customers. Recommender systems use several ways to make recommendations. Two ways are using more than the others: collaborative filtering and content-based filtering. In this study, a recommender system model based on collaborative filtering has proposed. Proposed model was endeavored to improve the customer profile in collaborative systems to enhance the recommender system ef… Show more

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Cited by 3 publications
(1 citation statement)
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“…To improve and strengthen their market position, retail chains are trying to invest considerable money in obtaining information about their customers. Julashokri et al (2011) reported that customer profile knowledge is an essential element of one-to-one marketing in marketing planning. Various models are often used in marketing planning to create suitable customer profiles, which Park and Chang (2009) argue can improve entire customer profiling systems.…”
Section: Introductionmentioning
confidence: 99%
“…To improve and strengthen their market position, retail chains are trying to invest considerable money in obtaining information about their customers. Julashokri et al (2011) reported that customer profile knowledge is an essential element of one-to-one marketing in marketing planning. Various models are often used in marketing planning to create suitable customer profiles, which Park and Chang (2009) argue can improve entire customer profiling systems.…”
Section: Introductionmentioning
confidence: 99%