# Interactive Semantic Featuring for Text Classification

arXiv: https://arxiv.org/abs/1606.07545 · HTML: https://mlsanity.com/paper/1606.07545/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jun 2016.

## Built on by (most cited first, 2 of 2)

- [Putting Humans in the Natural Language Processing Loop: A Survey](https://mlsanity.com/paper/2103.04044/) (2021)
- [Human-AI Interaction Design in Machine Teaching](https://mlsanity.com/paper/2206.05182/) (2022)

## Abstract (arXiv)

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.