Corpus ID: 9573100

Temporally Coherent Clustering of Student Data

@inproceedings{Klingler2016TemporallyCC,
  title={Temporally Coherent Clustering of Student Data},
  author={Severin Klingler and Tanja K{\"a}ser and B. Solenthaler and M. Gross},
  booktitle={EDM},
  year={2016}
}
  • Severin Klingler, Tanja Käser, +1 author M. Gross
  • Published in EDM 2016
  • Computer Science
  • The extraction of student behavior is an important task in educational data mining. A common approach to detect similar behavior patterns is to cluster sequential data. Standard approaches identify clusters at each time step separately and typically show low performance for data that inherently suffer from noise, resulting in temporally inconsistent clusters. We propose an evolutionary clustering pipeline that can be applied to learning data, aiming at improving cluster stability over multiple… CONTINUE READING
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