Temporal Analytics for Software Usage Models

@inproceedings{Andrei2017TemporalAF,
  title={Temporal Analytics for Software Usage Models},
  author={Oana Andrei and Muffy Calder},
  booktitle={SEFM Workshops},
  year={2017}
}
We address the problem of analysing how users actually interact with software. Users are heterogeneous: they adopt different usage patterns and each individual user may move between different patterns, from one interaction session to another, or even during an interaction session. For analysis, we require new techniques to model and analyse temporal data sets of logged interactions with the purpose of discovering, interpreting, and communicating meaningful patterns of usage. We define new… 
2 Citations
Interpreting Computational Models of Interactive Software Usage
TLDR
This work proposes new temporal analytics to model and analyse logged interactions, based on learning admixture Markov models and interpreting them using probabilistic temporal logic properties and model checking.

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