文章基本信息

标题：Review on Map and Reduced based Semantic Parsing of Open Street Map using KNN
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作者：Poonam Devi ; Rachna
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2018
卷号：6
期号：5
页码：5826-5831
DOI：10.15680/IJIRCCE.2018.0605099
出版社：S&S Publications
摘要：Support of privileged exploration on vast volumes of spatial information turns out to be progressively critical in numerous application spaces, incorporating geospatial issues in various fields, area based administrations, and rising logical applications that are progressively information and process escalated. The rise of monstrous scale spatial information is because of the expansion of savvy and pervasive situating advances, improvement of high determination imaging advances, and commitment from countless clients. There are two noteworthy difficulties for overseeing and questioning enormous spatial information to help spatial inquiries: the blast of spatial information, and the high computational intricacy of spatial inquiries. In this paper, we present Big Data Geospatial Information System – an adaptable and elite spatial information warehousing framework for running extensive scale spatial questions on Big Data. Big Data Geospatial Information System underpins numerous kinds of spatial questions on Map-per and Reducer through spatial parsing adjustable spatial inquiry and queries for mammoth extraction and parallel spatial question execution on Map-per and Reducer, and successful strategies for correcting question comes about through taking care of limit objects. Big Data Geospatial Information System uses worldwide tract categorize and adaptable on request neighbourhood spatial ordering to accomplish productive inquiry handling. Big Data Geospatial Information System is coordinated into Hive to help decisive spatial inquiries with an incorporated engineering. Our investigations have shown the high effectiveness of Big Data Geospatial Information System on inquiry reaction and high adaptability to keep running on product groups. Our similar examinations have demonstrated that execution of Big Data Geospatial Information System is keeping pace with parallel SDBMS and beats SDBMS for figure escalated questions. Big Data Geospatial Information System is accessible as an arrangement of library for handling spatial inquiries, and as an incorporated programming bundle in Hive over Big Data Ecosystem along-with machine learning amalgamated algorithm namely K-nearest neighbour (KNN) .
关键词：MapReduce (Map;per Reducer) Big Data; Hadoop; HIVE; Open Street Maps (OSM); Geographic Information Systems (GIS); Machine Readable Language; Semantic Parsing; K Nearest Neighbours (KNN); SDBMS (Spatial Database Management System);