...
首页> 外文期刊>International journal of handheld computing research >A Research Approach to Detect Unreliable Information in Online Professional Social Networks: Using Linkedln Mobile as an Example
【24h】

A Research Approach to Detect Unreliable Information in Online Professional Social Networks: Using Linkedln Mobile as an Example

机译:在线专业社交网络中检测不可靠信息的研究方法:以Linkedln Mobile为例

获取原文
获取原文并翻译 | 示例

摘要

Professional social network gives companies a platform to post hiring information and locate professional talents. However, the professional network has a great number of users who generate huge amount of information every day, which makes it difficult for the hiring company to distinguish reliability of users 'information and evaluate their professional abilities. In this context, this article bases on Linkedln Mobile as the online professional social network and proposes a research approach to effectively identify unreliable information and evaluate users 'abilities. First, the authors look for relevant social network profiles for a cross-site check Second, on a single professional social networking they site, the authors check the similarity between the user s background and his connections' backgrounds, to detect any possible unreliable information. Third, they propose an algorithm to rank the trustfulness of users 'recommendations based on a PageRank algorithm that was traditionally to evaluate the importance of web pages.
机译:专业的社交网络为公司提供了发布招聘信息和寻找专业人才的平台。但是,专业网络每天都有大量用户产生大量信息,这使得招聘公司很难区分用户信息的可靠性和评估他们的专业能力。在这种情况下,本文基于Linkedln Mobile作为在线专业社交网络,并提出了一种研究方法,可以有效地识别不可靠的信息并评估用户的能力。首先,作者寻找相关的社交网络配置文件以进行跨站点检查。其次,在他们所在的单个专业社交网络上,作者检查用户背景与其连接背景之间的相似性,以检测任何可能的不可靠信息。第三,他们提出了一种基于PageRank算法对用户推荐的信任度进行排名的算法,该算法通常用于评估网页的重要性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号