Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
Multidimensional Analysis Framework on Massive Data of Observations of Daily Living
verfasst von : Jianhua Lu, Baili Zhang, Xueyan Wang, Ningyun Lu
Erschienen in: Health Information Science
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Observations of daily living (ODLs) are cues that people attend to in the course of their everyday life, that inform them about their health. In order to better understand the ODLs, we propose a set of innovative multi-dimensional analysis concepts and methods. Firstly, the ODLs are organized as directed graphs according the “observation-property” relationships and the chronological order of observations, which represents all the information in a flexible way; Secondly, a novel concept, the structure dimension, is proposed to integrate into the traditional multidimensional analysis framework. From the structure dimension that consists of three granularities, vertices, edges and subgraphs, one can get a clearer view of the ODLs; Finally, the hierarchy of ODLs Cube is introduced, and the semantics of OLAP operations, Roll-up, Drill-down and Slice/dice, are redefined to accommodate the structure dimension. The proposed structure dimension and ODLs cube are effective for multidimensional analysis of ODLs.