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- W2018582844 abstract "The paper describes an improved method for automatic duplicate bug report detection based on new textual similarity features and binary classification. Using a set of new textual features, inspired from recent text similarity research, we train several binary classification models. A case study was conducted on three open source systems: Eclipse, Open Office, and Mozilla to determine the effectiveness of the improved method. A comparison is also made with current state-of-the-art approaches highlighting similarities and differences. Results indicate that the accuracy of the proposed method is better than previously reported research with respect to all three systems." @default.
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- W2018582844 date "2014-05-31" @default.
- W2018582844 modified "2023-10-14" @default.
- W2018582844 title "Improving the accuracy of duplicate bug report detection using textual similarity measures" @default.
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- W2018582844 doi "https://doi.org/10.1145/2597073.2597088" @default.
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