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Analyzing software reviews for software quality-based ranking

机译:分析软件评论以基于软件质量进行排名

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摘要

Software comparison reviews from users who have experience with the software are important information for software ranking. Software reviews may contain information in terms of software quality comparison such as, “Software A is better than the other in quality Q”. This information can be used for software quality ranking. This research presents an approach for software ranking from user reviews which composed of 3 main phases: user reviews gathering, user reviews analysis and software ranking. After user reviews gathering, a collection of user review is constructed and analyzed. The analysis consists of comparative relation extraction, quality classification and sentiment classification. We use keyword and grammatical relation to extract comparative relation. Keyword is also used for 5 types of quality classification; performance, reliability, security, usability and maintainability. Information from comparative relation is used for sentiment classification. Then, the ranking method is performed. From our experiment, we achieve a high value of f-measure for comparative relation extraction and quality classification. We also improve the accuracy of sentiment classification. Our proposed ranking result is statistically correlated to the expert judgment with 0.935 Pearson's correlation coefficient.
机译:来自具有软件经验的用户的软件比较评论是软件排名的重要信息。软件评论可能包含有关软件质量比较的信息,例如“软件A在质量Q方面优于其他软件”。此信息可用于软件质量排名。这项研究提出了一种从用户评论进行软件排名的方法,该方法包括3个主要阶段:用户评论收集,用户评论分析和软件排名。在收集用户评论之后,将构建并分析用户评论的集合。分析包括比较关系提取,质量分类和情感分类。我们使用关键词和语法关系来提取比较关系。关键字也用于5种类型的质量分类;性能,可靠性,安全性,可用性和可维护性。来自比较关系的信息用于情感分类。然后,执行排序方法。从我们的实验中,我们在比较关系提取和质量分类中获得了很高的f度量值。我们还提高了情感分类的准确性。我们提出的排名结果与专家判断的统计相关性为0.935皮尔逊相关系数。

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