Academic Journal
أعرض في EDS

Intrinsic dimensionality of human behavioral activity data.

التفاصيل البيبلوغرافية
العنوان: Intrinsic dimensionality of human behavioral activity data.
المؤلفون: Luana Fragoso, Tuhin Paul, Flaviu Vadan, Kevin G Stanley, Scott Bell, Nathaniel D Osgood
المصدر: PLoS ONE, Vol 14, Iss 6, p e0218966 (2019)
بيانات النشر: Public Library of Science (PLoS), 2019.
سنة النشر: 2019
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Patterns of spatial behavior dictate how we use our infrastructure, encounter other people, or are exposed to services and opportunities. Understanding these patterns through the analysis of data commonly available through commodity smartphones has become an important arena for innovation in both academia and industry. The resulting datasets can quickly become massive, indicating the need for concise understanding of the scope of the data collected. Some data is obviously correlated (for example GPS location and which WiFi routers are seen). Codifying the extent of these correlations could identify potential new models, provide guidance on the amount of data to collect, and even provide actionable features. However, identifying correlations, or even the extent of correlation, is difficult because the form of the correlation must be specified. Fractal-based intrinsic dimensionality directly calculates the minimum number of dimensions required to represent a dataset. We provide an intrinsic dimensionality analysis of four smartphone datasets over seven input dimensions, and empirically demonstrate an intrinsic dimension of approximately two.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1932-6203
Relation: https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0218966
URL الوصول: https://doaj.org/article/471cc3bad19a425eb25c4e94665178f3
رقم الانضمام: edsdoj.471cc3bad19a425eb25c4e94665178f3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19326203
DOI:10.1371/journal.pone.0218966