Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs

Natalia Díaz-Rodríguez; Aki Härmä; Rim Helaoui; Ignacio Huitzil; Fernando Bobillo; Umberto Straccia

Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs

Natalia Díaz-Rodríguez^*
, Aki Härmä
, Rim Helaoui
, Ignacio Huitzil
, Fernando Bobillo
, Umberto Straccia

^*Corresponding author for this work

Research output: Contribution to conference › Paper › Academic

Abstract

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.

Original language	English
Publication status	Published - 2017
Externally published	Yes
Event	6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017 - Long Beach, United States Duration: 8 Dec 2017 → 8 Dec 2017 Conference number: 6

Workshop

Workshop	6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017
Abbreviated title	AKBC 2017
Country/Territory	United States
City	Long Beach
Period	8/12/17 → 8/12/17

Cite this

Díaz-Rodríguez, N., Härmä, A., Helaoui, R., Huitzil, I., Bobillo, F., & Straccia, U. (2017). Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs. Paper presented at 6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017, Long Beach, United States.

@conference{721b4e7b1ac04d108a1fca180f451f80,

title = "Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs",

abstract = "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.",

author = "Natalia D{\'i}az-Rodr{\'i}guez and Aki H{\"a}rm{\"a} and Rim Helaoui and Ignacio Huitzil and Fernando Bobillo and Umberto Straccia",

note = "Funding Information: We acknowledge AAPELE.eu EU COST Action IC1303 and EU Erasmus+ Funding. I. Huitzil was partially funded by Universidad de Zaragoza – Santander Universidades (Ayudas de Movilidad para Latinoamericanos - Estudios de Doctorado). Publisher Copyright: {\textcopyright} AKBC Organizers 2017.; 6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017, AKBC 2017 ; Conference date: 08-12-2017 Through 08-12-2017",

year = "2017",

language = "English",

}

Díaz-Rodríguez, N, Härmä, A, Helaoui, R, Huitzil, I, Bobillo, F & Straccia, U 2017, 'Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs', Paper presented at 6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017, Long Beach, United States, 8/12/17 - 8/12/17.

Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs. / Díaz-Rodríguez, Natalia; Härmä, Aki; Helaoui, Rim et al.
2017. Paper presented at 6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017, Long Beach, United States.

Research output: Contribution to conference › Paper › Academic

TY - CONF

T1 - Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs

AU - Díaz-Rodríguez, Natalia

AU - Härmä, Aki

AU - Helaoui, Rim

AU - Huitzil, Ignacio

AU - Bobillo, Fernando

AU - Straccia, Umberto

N1 - Conference code: 6

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85128465107

M3 - Paper

AN - SCOPUS:85128465107

T2 - 6th Workshop on Automated Knowledge Base Construction, AKBC 2017 at the 31st Conference on Neural Information Processing Systems, NIPS 2017

Y2 - 8 December 2017 through 8 December 2017

ER -

Couch potato or gym addict? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs

Abstract

Workshop

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