Shallow Recurrent Neural Network for Personality Recognition in Source Code
نویسندگان
چکیده
Personality recognition in source code constitutes a novel task in the field of author profiling on written text. In this paper we describe our proposal for the PR-SOCO shared task in FIRE 2016, which is based on a shallow recurrent LSTM neural network that tries to predict five personality traits of the author given a source code fragment. Our preliminary results show that it should be possible to tackle the problem at hand with our approach but also that there is still room for improvement through more complex network architectures and training processes.
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تاریخ انتشار 2016