# Uncertainty in Ontology Matching: A Decision Rule-Based Approach

arXiv: https://arxiv.org/abs/1501.05724 · HTML: https://mlsanity.com/paper/1501.05724/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jan 2015.

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

- [Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing context](https://mlsanity.com/paper/2303.04548/) (2023)

## Abstract (arXiv)

Considering the high heterogeneity of the ontologies pub-lished on the web, ontology matching is a crucial issue whose aim is to establish links between an entity of a source ontology and one or several entities from a target ontology. Perfectible similarity measures, consid-ered as sources of information, are combined to establish these links. The theory of belief functions is a powerful mathematical tool for combining such uncertain information. In this paper, we introduce a decision pro-cess based on a distance measure to identify the best possible matching entities for a given source entity.