Personalization Of Mobile Learning Tools For Low-Income Populations

It states that participants used content based (bag of words, word n-grams, slang words, etc.), style based (POS, readability measures, punc- tuations etc.) features, and that

We have used Long short term memory neural network and some hand-crafted features for recognizing the age, gender, and dialects of the author of a tweet 3.. Keywords: Dialects,

This solution is an original neural network with soft stepwise regression (soft stagewise regression network) for recognizing age and sex. The network recognizes age and

Finally, this system applies the ensemble model and this machine learning technique is able to predict with 60 percent accuracy metric for age category and 83 percent

Thus, this research work is intended to consider the video-based age and gender recognition task as the problem of choosing the most reliable solution using the classifier fusion

Abstract. Research has shown that social influence is a strong motivator of behavior change. However, in persuasive technology research, limited studies exist showing

The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user.. This means training the system using the behavior of

Although the competi- tion stated that Author Profiling task would focus on cross-genre age and gender identification, we believed convenient to try different values of L using the