DBAIApr 20, 2013

A Markov Model for Ontology Alignment

arXiv:1304.5566v16 citations
Originality Synthesis-oriented
AI Analysis

This work addresses data integration challenges in Semantic Web technologies, but it is incremental as it builds upon an existing technique.

The authors tackled the problem of ontology alignment for integrating heterogeneous knowledge bases by proposing the Edge Confidence technique, which is a modification and improvement over the Similarity Flooding method.

The explosion of available data along with the need to integrate and utilize that data has led to a pressing interest in data integration techniques. In terms of Semantic Web technologies, Ontology Alignment is a key step in the process of integrating heterogeneous knowledge bases. In this paper, we present the Edge Confidence technique, a modification and improvement over the popular Similarity Flooding technique for Ontology Alignment.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes