UniNE at CLEF 2017: Author Profiling Reasoning


This paper describes and evaluates a supervised author profiling model. The suggested strategy can be adapted without any problem to various languages (such as Arabic, English, Spanish, and Portuguese). As features, we suggest using the m most frequent terms of the query text (isolated words and punctuation symbols with m at most 200). Applying a simple… (More)

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