Quality assessment of collaborative content with minimal information

机译：以最少的信息进行协作内容的质量评估

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Content generated by users is one of the most interesting phenomena of published media. However, the possibility of unrestricted edition is a source of doubts about its quality. This issue has motivated many studies on how to automatically assess content quality in collaborative web sites. Generally, these studies use machine learning techniques to combine large number of quality indicators into a single value representing the overall quality of the document. This need for a high number of indicators, however, has detrimental implications both on the efficiency and on the effectiveness of the quality assessment algorithms. In this work, we exploit and extend a feature selection method based on the SPEA2 multi-objective genetic algorithm. Results show that we can reduce the feature set to a fraction of 15% through 25% of the original, while obtaining error rates comparable to the state of the art.

机译：用户生成的内容是已发布媒体中最有趣的现象之一。但是，无限制版本的可能性令人质疑其质量。这个问题激发了许多关于如何自动评估协作网站中内容质量的研究。通常，这些研究使用机器学习技术将大量质量指标组合为一个代表文档整体质量的单个值。但是，对大量指标的需求对质量评估算法的效率和有效性都具有不利影响。在这项工作中，我们探索并扩展了基于SPEA2多目标遗传算法的特征选择方法。结果表明，我们可以将特征集减少到原始特征集的15％到25％，同时获得与现有技术相当的错误率。

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来源
《2014 IEEE/ACM Joint Conference on Digital Libraries》|2014年|201-210|共10页
会议地点 London(GB)
作者
Dalip D.H.; Lima H.; Goncalves M.A.; Cristo M.; Calado P.;
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作者单位

Dept. of Comput. Sci., UFMG, Belo Horizonte, Brazil;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Web sites; genetic algorithms; information analysis; learning (artificial intelligence); SPEA2 multiobjective genetic algorithm; collaborative content; collaborative web sites; content quality; feature selection method; machine learning techniques; minimal information; published media; quality assessment; quality assessment algorithms; Electronic publishing; Genetic algorithms; History; Information services; Internet; Quality assessment; Sociology; Feature Selection; Genetic Algorithm; Machine Learning; Quality Assessm;

机译：网站;遗传算法;信息分析;学习（人工智能）; SPEA2多目标遗传算法;协作内容;协作网站;内容质量;功能选择方法;机器学习技术;最少信息;发布的媒体;质量评估;质量评估算法;电子出版;遗传算法;历史;信息服务;互联网;质量评估;社会学;特征选择;遗传算法;机器学习;质量评估;

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Quality assessment of collaborative content with minimal information

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