# SmartReviews: Towards Human- and Machine-actionable Reviews

arXiv: https://arxiv.org/abs/2107.03816 · HTML: https://mlsanity.com/paper/2107.03816/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2021.

## Built on by (most cited first, 1 of 1)

- [From Keywords to Structured Summaries: Streamlining Scholarly Information Access](https://mlsanity.com/paper/2402.14622/) (2024)

## Abstract (arXiv)

Review articles summarize state-of-the-art work and provide a means to organize the growing number of scholarly publications. However, the current review method and publication mechanisms hinder the impact review articles can potentially have. Among other limitations, reviews only provide a snapshot of the current literature and are generally not readable by machines. In this work, we identify the weaknesses of the current review method. Afterwards, we present the SmartReview approach addressing those weaknesses. The approach pushes towards semantic community-maintained review articles. At the core of our approach, knowledge graphs are employed to make articles more machine-actionable and maintainable.