基于大数据的信息可信度建模方法研究

Yijun Liulst, Wenqi Cai, Zhigang Xu
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摘要

随着大数据时代的到来,数据量呈指数级增长。数据管理、分析和应用的难度也成倍增加。数据的真实性和可信度变得越来越重要。真实可靠的信息可以为人们的决策提供重要的帮助。但在很多情况下,数据的真实性仍然需要判断和确认。提出了一种自动分析大数据可信度的建模方法。本文以网上下载的数百份公开简历为数据源,提出了一种基于年龄、学历、职位、身份的简历建模方法。结果客观有效。该方法探索了传统简历信息人工审核方式的转型,突破了大数据时代简历信息海量增长导致无法人工审核的问题,为大数据自动评估可信度建模分析探索了新思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Information Credibility Modeling Method Based on Big Data
With the advent of the era of big data, the amount of data is growing exponentially. The difficulty of data management, analysis and application is also multiplied. The authenticity and credibility of data become more and more important. Authentic and reliable information can provide important help for people’s decision-making. But in many cases, the authenticity of the data still needs to be judged and confirmed. This paper proposes a modeling method for automatically analyzing the credibility of big data. Taking hundreds of public resumes downloaded from the Internet as data sources, this paper proposes a modeling method based on age, education, position and identity to analyze the resume. The results were objective and effective. This method explores the transformation of traditional manual review method of resume information, breaks through the problem that cannot be manually reviewed due to the massive growth of resume information in the era of big data, and explores new ideas for modeling and analyzing the credibility of automatic evaluation of big data.
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