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Author profiling is one of the active researches in the field of data mining. Rather than only concentrated on the syntactic as well as stylometric features, this paper describes about more relevant features which will profile the authors more accurately. Readability metrics, vocabulary richness, and emotional status are the features which are taken into consideration. Age and gender are detected as the metrics for author profiling. Stylometry is defined by using deep learning algorithm. This approach has attained an accuracy of 97.7% for gender and 90.1% for age prediction.
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- Stylometry Detection Using Deep Learning
O. P. Harilal
N. K. Suchetha
- Springer Singapore
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