# Assessing Semantic Annotation Activities with Formal Concept Analysis

arXiv: https://arxiv.org/abs/2501.11123 · HTML: https://mlsanity.com/paper/2501.11123/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 95 references that are in the map.
- First posted on arXiv 19 Jan 2025.

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

- [Ontology-Enhanced Educational Annotation Activities](https://mlsanity.com/paper/2501.12943/) (2025)
- [A review of annotation classification tools in the educational domain](https://mlsanity.com/paper/2501.14976/) (2025)
- [A Variability-Based Framework for Interpretable Naming in Formal and Relational Concept Analysis](https://mlsanity.com/paper/2606.08477/) (2026)

## Abstract (arXiv)

This paper describes an approach to assessing semantic annotation activities based on formal concept analysis (FCA). In this approach, annotators use taxonomical ontologies created by domain experts to annotate digital resources. Then, using FCA, domain experts are provided with concept lattices that graphically display how their ontologies were used during the semantic annotation process. In consequence, they can advise annotators on how to better use the ontologies, as well as how to refine them to better suit the needs of the semantic annotators. To illustrate the approach, we describe its implementation in @note, a Rich Internet Application (RIA) for the collaborative annotation of digitized literary texts, we exemplify its use with a case study, and we provide some evaluation results using the method.