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  • 标题:Retrieving Relevant Documents and Scoring the Candidate Keyword Queries at the Partition Level with Using Ba and Pa Algorithms
  • 本地全文:下载
  • 作者:V Uma Rani ; Sunitha Vanamala ; K. Soumya
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2017
  • 卷号:6
  • 期号:8
  • 页码:17229
  • DOI:10.15680/IJIRSET.2017.0608227
  • 出版社:S&S Publications
  • 摘要:This Keyword suggestion are the most basic feature of the search engine. Naive users don’t know howto express their queries correctly most of the time queries square measure short and unambiguous; keyword suggestionin internet search assists users to access relevant data. Data are going to be additional relevant if location of the users isconsidered. The location aware keyword (LKS) question suggestion technique helps retrieve documents that relates toinformation provides by user and location wherever the user is found. But the search results’ connectedness isunderstood to be related with the spatial proximity of the user. During this paper we offer transient study all thetechniques for the keyword suggestions and discuss concerning location-aware keyword question suggestionframework and improved Partition based mostly algorithm.
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