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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bird, Christian Menzies, Tim Zimmermann, Thomas |
| Copyright Year | 2013 |
| Description | Author affiliation: Microsoft Research, USA (Bird, Christian; Zimmermann, Thomas) || West Virginia University, USA (Menzies, Tim) |
| Abstract | Data scientists in software engineering seek insight in data collected from software projects to improve software development. The demand for data scientists with domain knowledge in software development is growing rapidly and there is already a shortage of such data scientists. Data science is a skilled art with a steep learning curve. To shorten that learning curve, this workshop will collect best practices in form of data analysis patterns, that is, analyses of data that leads to meaningful conclusions and can be reused for comparable data. In the workshop we compiled a catalog of such patterns that will help experienced data scientists to better communicate about data analysis. The workshop was targeted at experienced data scientists and researchers and anyone interested in how to analyze data correctly and efficiently in a community accepted way. |
| Starting Page | 1517 |
| Ending Page | 1518 |
| File Size | 156386 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781467330732 |
| e-ISBN | 9781467330763 |
| DOI | 10.1109/ICSE.2013.6606765 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-18 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Conferences Software Data analysis Software engineering Data mining Sociology Statistics software intelligence data science software engineering data mining predictive analytics business intelligence machine learning big data smart data software analytics |
| Content Type | Text |
| Resource Type | Article |
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