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Toward of Conceptual Recommender Service for Big Data Platform

机译:对大数据平台的概念推荐服务

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摘要

Recommendation system (RS) is an information technology that commerce vendors have adopted so that customer can receive suggestions on the items that they will find interesting. These systems are a valuable assistant to the user purchase decisions, and provide quality of push service.Traditionally RS have been designed using a centralized system, but information service is growing huge and rapid scalability very big. Next generation technology like Cloud Computing (CC) and Big Data Environment (BDE) has handle massive data and can support enormous processing. Nevertheless,analytic technologies are lacking in capabilities when processing big data. Accordingly we will design to conceptual service model and propose new algorithm and user adaptation on recommendation system for big data environment.
机译:推荐系统(RS)是商务供应商采用的信息技术,以便客户可以收到对他们将找到有趣的项目的建议。 这些系统是用户购买决策的宝贵助手,并提供推送服务的质量。使用集中系统设计了RS的标准,但信息服务越来越大而快速可扩展性非常大。 下一代技术,如云计算(CC)和大数据环境(BDE)具有处理大量数据,可以支持巨大的处理。 尽管如此,在处理大数据时缺乏分析技术。 因此,我们将设计为概念服务模型,并提出了新的大数据环境推荐系统的新算法和用户适应。

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