{"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}
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.