PlumX Metrics
Embed PlumX Metrics

Active learning and mapping: A survey and conception of a new stochastic methodology for high throughput materials discovery

Advanced Methods and Applications in Chemoinformatics: Research Progress and New Applications, Page: 111-138
2011
  • 0
    Citations
  • 0
    Usage
  • 4
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

Book Chapter Description

The data mining technology increasingly employed into new industrial processes, which require automatic analysis of data and related results in order to quickly proceed to conclusions. However, for some applications, an absolute automation may not be appropriate. Unlike traditional data mining, contexts deal with voluminous amounts of data, some domains are actually characterized by a scarcity of data, owing to the cost and time involved in conducting simulations or setting up experimental apparatus for data collection. In such domains, it is hence prudent to balance speed through automation and the utility of the generated data. The authors review the active learning methodology, and a new one that aims at generating successively new samples in order to reach an improved final estimation of the entire search space investigated according to the knowledge accumulated iteratively through samples selection and corresponding obtained results, is presented. The methodology is shown to be of great interest for applications such as high throughput material science and especially heterogeneous catalysis where the chemists do not have previous knowledge allowing to direct and to guide the exploration. © 2012, IGI Global.

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know