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  • 标题:Privacy for Semantic Web Mining using Advanced DSA � Spatial LBS Case Study
  • 本地全文:下载
  • 作者:Dr.D.Sravan Kumar ; M.Upendra Kumar
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2010
  • 卷号:2
  • 期号:3
  • 页码:691-694
  • 出版社:Engg Journals Publications
  • 摘要:The Web Services paradigm promises to enable rich flexible and dynamic interoperation of highly distributed, heterogeneous network enabled services. The idea of Web Services Mining that it makes use of the findings in the field of data mining and applies them to the world of Web Services. The emerging concept of Semantic Web Services aims at more sophisticated Web Services technologies: on basis of Semantic Description Frameworks, Intelligent mechanisms are envisioned for Discovery, Composition, and contracting of Web Services. The aim of semantic web is not only to support to access information on the web but also to support its usage. Geospatial Semantic Web is an augmentation to the Semantic Web that adds geospatial abstractions, as well as related reasoning, representation and query mechanisms. Web Service Security represents a key requirement for today�s distributed interconnected digital world and for the new generations, Web 2.0 and Semantic Web. To date, the problem of security has been investigated very much in the context of standardization efforts; Personal judgments are made usually based on the sensitivity of the information and the reputation of the party to which the information is to be disclosed. On the privacy front, this means that privacy invasion would net more quality and sensitive personal information. In this paper, we had implemented a case study on integrated privacy issues of Spatial Semantic Web Services Mining. Initially we improved privacy of Geospatial Semantic Layer. Finally, we implemented a Location Based System and improved its digital signature capability, using advanced Digital Signature standards.
  • 关键词:Semantic Web; Spatial Web mining; Scientific Data Mining; Privacy; Advanced Digital Signature Standards.
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