文章基本信息

标题：Keyword Search and Geographic aspect Spatial Top k Search
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作者：Harsh Anand ; Monika Kumari ; Ashwini Vidyadhar Hiremath 等
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：2017
卷号：5
期号：4
页码：8907
DOI：10.15680/IJIRCCE.2017.05040333
出版社：S&S Publications
摘要：with the increasing pervasiveness of the geo-positioning technologies and geo-location services, therearea large amount of spatio-textual objects offered in several applications. That type of data provides the placementconnected data relating to the amount of hotels, Hospitals. This data obtained by the keyword search. This explores thehelpful data relating to the actual locations or places. K-nearest neighbor (k-NN) queries Most of the presentapproaches to the current drawback are processing of sets of TOPK-SK queries. Supported the inverted index and alsothe linear quad tree, we propose a completely unique index structure. To address this drawback, we propose a set ofsolutions which will support inverted linear quad tree process of k-NN queries. We propose initial new index structurereferred to as Dynamic Strip Index (DSI), which may higher adapt to completely different information distributionsthan exiting grid indexes. We proposed investigate the matter of conducting prime k spatial keyword search. Weproposed to additional propose a distributed k-NN search (DKNN) rule supported DSI. The advances of GPStechnology and wide-ranging usage of wireless communication devices have expedited the gathering of huge quantityof spatiotemporal information. Of interest group is information related to the location keyword.
关键词：Spatial; Keyword; Batch; k nearest neighbour query; spatial keyword query; scalability