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arXiv · 1606.07545

Interactive Semantic Featuring for Text Classification

Camille Jandot·Patrice Simard·Max Chickering·David Grangier·Jina Suh
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Abstract

In text classification, dictionaries can be used to define human-comprehensible features. We propose an improvement to dictionary features called smoothed dictionary features. These features recognize document contexts instead of n-grams. We describe a principled methodology to solicit dictionary features from a teacher, and present results showing that models built using these human-comprehensible features are competitive with models trained with Bag of Words features.

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Camille Jandot, Patrice Simard, Max Chickering, David Grangier, Jina Suh. 2016-06-24. Interactive Semantic Featuring for Text Classification. https://arxiv.org/abs/1606.07545

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