# Classifying concepts via visual properties

arXiv: https://arxiv.org/abs/2105.09422 · HTML: https://mlsanity.com/paper/2105.09422/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 27 references that are in the map.
- First posted on arXiv 19 May 2021.

## Builds on (most cited first, 2 of 2)

- [Continual egocentric object recognition](https://mlsanity.com/paper/1912.05029/) (2019)
- [Towards Visual Semantics](https://mlsanity.com/paper/2104.12379/) (2021)

## Built on by (most cited first, 3 of 3)

- [Using Linguistic Typology to Enrich Multilingual Lexicons: the Case of Lexical Gaps in Kinship](https://mlsanity.com/paper/2204.05049/) (2022)
- [Lexical Diversity in Kinship Across Languages and Dialects](https://mlsanity.com/paper/2308.13056/) (2023)
- [Crowdsourcing Lexical Diversity](https://mlsanity.com/paper/2410.23133/) (2024)

## Abstract (arXiv)

We assume that substances in the world are represented by two types of concepts, namely substance concepts and classification concepts, the former instrumental to (visual) perception, the latter to (language based) classification. Based on this distinction, we introduce a general methodology for building lexico-semantic hierarchies of substance concepts, where nodes are annotated with the media, e.g.,videos or photos, from which substance concepts are extracted, and are associated with the corresponding classification concepts. The methodology is based on Ranganathan's original faceted approach, contextualized to the problem of classifying substance concepts. The key novelty is that the hierarchy is built exploiting the visual properties of substance concepts, while the linguistically defined properties of classification concepts are only used to describe substance concepts. The validity of the approach is exemplified by providing some highlights of an ongoing project whose goal is to build a large scale multimedia multilingual concept hierarchy.