| Publication Type |
Conference Paper |
| Authors |
Julia Seiter, Oliver Amft, Gerhard Tröster |
| Title |
Assessing Topic Models: How to Obtain Robustness? |
| Abstract |
In this work we investigate the influence of varying daily activity dataset characteristics on topic model performance stability for daily routine discovery. For this purpose, we denote a set of key dataset properties that influence the experimental design regarding recording, as well as data pre-processing steps. Using generated daily activity datasets, we identified optimal topic model stability for particular dataset properties. Results indicated that topic model routine duration should exceed document size by a factor of more than two. Recording durations of more than 9 days were required for a set of four routines and activity primitive overlap may not exceed 5%. |
| Date |
2012 |
| Proceedings Title |
AwareCast 2012: Workshop on Recent Advances in Behavior Prediction and Pro-active Pervasive Computing |
| Full Text |
PDF |
