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Adel Alharbi (#DemographicGroupClassification)
Abstract:
Interacting with smart devices is a... https://t.co/aOc6dK0zM3
@Dr__Melfi @fmalanazi @DrAhmadAlShayea @fayez_malki @FCITKAU @mbt3th @naifco #DemographicGroupClassification ูุงููุงุก ูุธุฑู ุจุณูุทุฉ ุนู ุงูู
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Read more about our conference paper that will be hold in (ICMLA), December 9-11, 2015 #DemographicGroupClassification
The study developed an Android application to collect and store the behavioral data #DemographicGroupClassification
The study collected data from twenty-two participants and used one device which was ASUS MeMO (ME173X) #DemographicGroupClassification
The study noted the user genders from the finger position features as shown below #DemographicGroupClassification
The accuracy rates: genders 94%, ages 88%,
languages 96%, operating system types 93%,
and nationalities 92% #DemographicGroupClassification
The research methodology developed the multi-fusion (MF) data model to combined all behavioral models #DemographicGroupClassification
An example of the decision tree classifier using the PCA values for the user genders #DemographicGroupClassification
Benefit 3: Enable companies to deliver services more efficiently #DemographicGroupClassification
Benefit 2: Allow for customized delivery of commercial or social networking services #DemographicGroupClassification
Benefit 1: Improve the application security #DemographicGroupClassification
The study used two classification algorithms which are principle component analysis (PCA) and decision tree #DemographicGroupClassification
Future work 3: Many validation and evaluation techniques could be applied in here #DemographicGroupClassification
Future work 2: Continue collecting data to gain more distinct data #DemographicGroupClassification
Future work 1: Additional investigation in machine learning techniques should be consider #DemographicGroupClassification
This work was approved by SMU Research Compliance at SMU in Dallas, TX #DemographicGroupClassification
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