| 書目名稱 | Computational Discovery of Scientific Knowledge |
| 副標題 | Introduction, Techni |
| 編輯 | Sa?o D?eroski,Ljup?o Todorovski |
| 視頻video | http://file.papertrans.cn/233/232245/232245.mp4 |
| 叢書名稱 | Lecture Notes in Computer Science |
| 圖書封面 |  |
| 描述 | .Advances in technology have enabled the collection of data from scientific observations, simulations, and experiments at an ever-increasing pace. For the scientist and engineer to benefit from these enhanced data collecting capabilities, it is becoming clear that semi-automated data analysis techniques must be applied to find the useful information in the data. Computational scientific discovery methods can be used to this end: they focus on applying computational methods to automate scientific activities, such as finding laws from observational data. In contrast to mining scientific data, which focuses on building highly predictive models, computational scientific discovery puts a strong emphasis on discovering knowledge represented in formalisms used by scientists and engineers, such as numeric equations and reaction pathways. ..This state-of-the-art survey provides an introduction to computational approaches to the discovery of scientific knowledge and gives an overview of recent advances in this area, including techniques and applications in environmental and life sciences. The 15 articles presented are partly inspired by the contributions of the International Symposium on Com |
| 出版日期 | Book 2007 |
| 關鍵詞 | DOM; Simulation; automated modeling; bioinformatics; biomedical applications; constraint-based mining; dat |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-540-73920-3 |
| isbn_softcover | 978-3-540-73919-7 |
| isbn_ebook | 978-3-540-73920-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 |
| issn_series | 0302-9743 |
| copyright | Springer-Verlag Berlin Heidelberg 2007 |
|Archiver|手機版|小黑屋|
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