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Computer Sciences, Robotics and automatic control
Activity discovery (AD) is the unsupervised process of discovering activities in data produced from streaming sensor networks that are recording the actions of human subjects. One major challenge for AD systems is interleaving, the tendency for people to carry out multiple activities at a time a parallel. Following on from our previous work, we continue to investigate AD in interleaved datasets, with a view towards progressing the state-of-the-art for AD.
Rogers, E., Ross, R.J., & Kelleher, J.D. (2017). Tackling the interleaving problem in activity discovery. Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017. doi:10.1007/978-3-319-61578-3_47
Presented at the doctoral consortium of the 15th International Conference on Practical Applications of Agents and Multi-Agent Systems, Porto, Portugal, June 2017.