A machine learning method for automatic copyright notice identification of source files
| Autor: | German M. Daniel, Shi Qiu, Katsuro Inoue |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
02 engineering and technology Machine learning computer.software_genre German Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Software maintenance Notice business.industry Volume (computing) 020206 networking & telecommunications Open source software language.human_language Identification (information) Hardware and Architecture language Software copyright 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business computer Software |
| Zdroj: | IEICE Transactions on Information and Systems. (12):2709-2712 |
| ISSN: | 1745-1361 2709-2712 |
| Popis: | Shi QIU, German M. DANIEL, Katsuro INOUE, A Machine Learning Method for Automatic Copyright Notice Identification of Source Files, IEICE Transactions on Information and Systems, 2020, Volume E103.D, Issue 12, Pages 2709-2712, Released December 01, 2020, Online ISSN 1745-1361, Print ISSN 0916-8532, https://doi.org/10.1587/transinf.2020EDL8089, https://www.jstage.jst.go.jp/article/transinf/E103.D/12/E103.D_2020EDL8089/_article/-char/en. For Free and Open Source Software (FOSS), identifying the copyright notices is important. However, both the collaborative manner of FOSS project development and the large number of source files increase its difficulty. In this paper, we aim at automatically identifying the copyright notices in source files based on machine learning techniques. The evaluation experiment shows that our method outperforms FOSSology, the only existing method based on regular expression. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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