论文信息 - Language Variety and Gender Classification for Author Profiling in PAN 2017

Language Variety and Gender Classification for Author Profiling in PAN 2017

We describe the method of Author Profiling task. The task deals with study of profile aspects like gender and language variety. We explore an approach of using high-order char n-grams as features and logistic regression as a classifier for all subtasks. This approach appears to be simple and effective for the task. We also investigated feature importances and low-dimensional embeddings of the data.

Alexey Romanov | Alexander Ogaltsov

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