Recency-Based Updating and Dynamic Management of Contextual Rules
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-88530-4_7
Reference8 articles.
1. Sarker, I. H., Colman, A., & Han, J. (2019). Recencyminer: mining recency-based personalized behavior from contextual smartphone data. Journal of Big Data, 6(1), 1–21.
2. Lee, S., Seo, J., & Lee, G. (2010, April). An adaptive speed-call list algorithm and its evaluation with ESM. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2019–2022).
3. Phithakkitnukoon, S., Dantu, R., Claxton, R., & Eagle, N. (2011). Behavior-based adaptive call predictor. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 6(3), 1–28.
4. Sarker, I. H., Colman, A., Kabir, M. A., & Han, J. (2018). Individualized time-series segmentation for mining mobile phone user behavior. The Computer Journal, 61(3), 349–368.
5. Halvey, M., Keane, M. T., & Smyth, B. (2006). Time based patterns in mobile-internet surfing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 31–34).
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