Hadoop and Hive Inspecting Maintenance of Mobile Application for Groceries Expenditure

Rao Mr, Logeshwari Ms, Loganathan Mr
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Abstract

Numerous movable applications on secure groceries expenditure and e-health have designed recently. Health aware clients respect such applications for secure groceries expenditure, particularly to avoid irritating groceries and added substances. However, there is the lack of a complete database including organized or unstructured information to help such applications. In the paper propose the Multiple Scoring Frameworks (MSF), a healthy groceries expenditure search service for movable applications using Hadoop and MapReduce (MR). The MSF works in a procedure behind a portable application to give a search service for data on groceries and groceries added substances. MSF works with similar logic from a web search engine (WSE) and it crawls over Web sources cataloguing important data for possible utilize in reacting to questions from movable applications. MSF outline and advancement are featured in the paper during its framework design, inquiry understanding, its utilization of the Hadoop/MapReduce infrastructure, and activity contents.
杂货消费移动应用的Hadoop和Hive巡检维护
最近设计了许多关于安全杂货支出和电子医疗的移动应用程序。有健康意识的客户尊重这样的应用程序,以确保食品杂货支出,特别是避免刺激性食品杂货和添加的物质。然而,缺乏一个完整的数据库,包括有组织的或非结构化的信息来帮助这些应用程序。本文提出了多重评分框架(MSF),这是一个使用Hadoop和MapReduce (MR)为可移动应用程序提供的健康杂货支出搜索服务。MSF在一个便携应用程序背后工作,为食品杂货和食品杂货添加物质的数据提供搜索服务。MSF使用来自web搜索引擎(WSE)的类似逻辑,它在web源上爬行,对重要数据进行编目,以便可能利用这些数据对来自可移动应用程序的问题作出反应。本文从MSF的框架设计、查询理解、对Hadoop/MapReduce基础设施的利用、活动内容等方面介绍了MSF的概况和进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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