Díaz Rodríguez N., Harma A., Huitzil I., Bobillo F., Straccia U, Helaoui R.
Semantic lifestyle profiling Fuzzy Description Logics
Automatic lifestyle profiling to categorize users according to their daily routine-based lifestyles is an unexplored area. Despite the current trends on having wearable devices that generate large amounts of heterogeneous data, figuring out the lifestyle patterns of people is not a trivial task. We present Lifestyles-KG, a knowledge graph (fuzzy ontology) for semantic reasoning from wearable sensors. It can serve as a pre-processing taxonomical step that can be integrated into further prediction techniques for intuitively categorizing fuzzy lifestyle concepts, treats or profiles. The ultimate aim is to help tasks such as long-term human behavior classification and consequently, improve virtual coaching or customize lifestyle recommendation and intervention programs from free form non-labelled sensor data.
Source: AKBC-17 - 6th Workshop on Automated Knowledge Base Construction, colocated with Thirty-First Annual Conference on Neural Information Processing Systems (NIPS-17), Long Beach, California, USA, December 8th, 2017
@inproceedings{oai:it.cnr:prodotti:380261, title = {Couch potato or gym addict? Semantic lifestyle profiling with wearables and knowledge graphs}, author = {Díaz Rodríguez N. and Harma A. and Huitzil I. and Bobillo F. and Straccia U and Helaoui R.}, booktitle = {AKBC-17 - 6th Workshop on Automated Knowledge Base Construction, colocated with Thirty-First Annual Conference on Neural Information Processing Systems (NIPS-17), Long Beach, California, USA, December 8th, 2017}, year = {2017} }