在无线移动网络管理中最大限度地提高关键词分析框架的效率

Q3 Business, Management and Accounting International Journal of Enterprise Network Management Pub Date : 2020-03-06 DOI:10.1504/ijenm.2020.10027440
K. Geetha, A. Kannan
{"title":"在无线移动网络管理中最大限度地提高关键词分析框架的效率","authors":"K. Geetha, A. Kannan","doi":"10.1504/ijenm.2020.10027440","DOIUrl":null,"url":null,"abstract":"Nowadays, data analytics in spatial database objects are associated with keywords. In the past decade, searching the keyword was a major focusing and active area to the researchers within the database server and information retrieval community in various applications. In recent years, the maximising the availability and ranking the most frequent keyword items evaluation in the spatial database are used to make the decision better. This motivates to carry out research towards of closest keyword cover search, which is also known as fine tuned keyword cover search methodology; it considers both inter object distance and keyword ranking of items in the spatial environment. Baseline algorithm derived in this area has its own drawbacks. While searching the keyword increases, the query result performance can be minimised gradually by generating the candidate keyword cover. To resolve this problem a new scalable methodology can be proposed in this paper.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Maximising the efficiency of keyword analytics framework in wireless mobile network management\",\"authors\":\"K. Geetha, A. Kannan\",\"doi\":\"10.1504/ijenm.2020.10027440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, data analytics in spatial database objects are associated with keywords. In the past decade, searching the keyword was a major focusing and active area to the researchers within the database server and information retrieval community in various applications. In recent years, the maximising the availability and ranking the most frequent keyword items evaluation in the spatial database are used to make the decision better. This motivates to carry out research towards of closest keyword cover search, which is also known as fine tuned keyword cover search methodology; it considers both inter object distance and keyword ranking of items in the spatial environment. Baseline algorithm derived in this area has its own drawbacks. While searching the keyword increases, the query result performance can be minimised gradually by generating the candidate keyword cover. To resolve this problem a new scalable methodology can be proposed in this paper.\",\"PeriodicalId\":39284,\"journal\":{\"name\":\"International Journal of Enterprise Network Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Enterprise Network Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijenm.2020.10027440\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Enterprise Network Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijenm.2020.10027440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 0

摘要

目前,空间数据库对象的数据分析与关键词相关。在过去的十年中,关键字搜索是数据库服务器和信息检索界在各种应用中研究人员关注和活跃的一个主要领域。近年来,利用空间数据库中可用性最大化和对最频繁的关键词项目进行排序来进行决策。这激发了对最接近关键字封面搜索的研究,也称为微调关键字封面搜索方法;它同时考虑了空间环境中物体间的距离和物体的关键词排序。这方面的基线算法有其自身的缺陷。当搜索关键字增加时,可以通过生成候选关键字覆盖来逐步降低查询结果的性能。为了解决这一问题,本文提出了一种新的可扩展方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Maximising the efficiency of keyword analytics framework in wireless mobile network management
Nowadays, data analytics in spatial database objects are associated with keywords. In the past decade, searching the keyword was a major focusing and active area to the researchers within the database server and information retrieval community in various applications. In recent years, the maximising the availability and ranking the most frequent keyword items evaluation in the spatial database are used to make the decision better. This motivates to carry out research towards of closest keyword cover search, which is also known as fine tuned keyword cover search methodology; it considers both inter object distance and keyword ranking of items in the spatial environment. Baseline algorithm derived in this area has its own drawbacks. While searching the keyword increases, the query result performance can be minimised gradually by generating the candidate keyword cover. To resolve this problem a new scalable methodology can be proposed in this paper.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Enterprise Network Management
International Journal of Enterprise Network Management Business, Management and Accounting-Management of Technology and Innovation
CiteScore
0.90
自引率
0.00%
发文量
28
期刊最新文献
Multi-tier firm-level analysis of global auto supply chain: centrality and financial performance Development of coating material for low carbon steels using MCDM Multi-objective optimisation of wear process parameters of 413/fly ash composites using grey relational analysis Fashion market segmentation using Facebook: an empirical approach Development of coating material for low carbon steels using MCDM
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1