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Mining Human Behavior for Health Promotion

Overview of attention for article published in Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, January 2015
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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2 X users

Citations

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17 Dimensions

Readers on

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22 Mendeley
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Title
Mining Human Behavior for Health Promotion
Published in
Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, January 2015
DOI 10.1109/embc.2015.7319529
Pubmed ID
Authors

Oresti Banos, Jaehun Bang, Taeho Hurl, Muhammad Hameed Siddiqil, Huynh-The Thien, La-Ba Vui, Wajahat Ali Khan, Taqdir Ali, Claudia Villalonga, Sungyoung Lee

Abstract

The monitoring of human lifestyles has gained much attention in the recent years. This work presents a novel approach to combine multiple context-awareness technologies for the automatic analysis of people's conduct in a comprehensive and holistic manner. Activity recognition, emotion recognition, location detection, and social analysis techniques are integrated with ontological mechanisms as part of a framework to identify human behavior. Key architectural components, methods and evidences are described in this paper to illustrate the interest of the proposed approach.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Lecturer 3 14%
Student > Ph. D. Student 3 14%
Student > Bachelor 2 9%
Researcher 2 9%
Other 6 27%
Unknown 2 9%
Readers by discipline Count As %
Computer Science 9 41%
Nursing and Health Professions 3 14%
Engineering 3 14%
Medicine and Dentistry 3 14%
Sports and Recreations 1 5%
Other 1 5%
Unknown 2 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 September 2016.
All research outputs
#16,584,977
of 25,382,440 outputs
Outputs from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#2,094
of 4,376 outputs
Outputs of similar age
#207,644
of 359,549 outputs
Outputs of similar age from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#95
of 234 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,376 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 359,549 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 234 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.