Volume 7 - Issue 1
Semantic Similarity Calculation Method using Information Contents-based Edge Weighting
- Sunghwan Jeong
Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 440-746, Korea
s103119@skku.edu
- Jun Hyeok Yim
Soosan INT Co., 10, Bamgogae-ro 1-gil, Gangnam-gu, Seoul 06349, Korea
gogo1525@soosan.co.kr
- Hyun Jung Lee
Yonsei Institute of Convergence Technology, 162-1, Songdo-dong, Yeonsu-gu, Incheon, Korea
hjlee5249@gmail.com
- Mye Sohn
Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 440-746, Korea
myesohn@skku.edu
Keywords: Hybrid semantic similarity, Ontology, Edge-based semantic similarity, Information Contentsbased semantic similarity
Abstract
In this paper, we propose Semantic Similarity calculation measurement using INformation contents
on EdGEs of ontology (SSINEGE) which is a hybrid edge- and information contents-based methodology.
SSINEGE is devised to solve the limitation of the applying the same weighted edges by edgebased
similarity. So, SSINEGE adopts information-contents theory to calculate the varied weights
of edges. The varied weighted edges by SSINEGE can also solve a problem with the same degree
of similarity for all pairs of concepts that are sharing a same Least Common Subsumer (LCS).
To minimize the overlapped information-contents on the weighted, SSINEGE adopts the conceptual
path between concepts instead of depths of the ontology. To verify the superiority of SSINEGE,
we compared SSINEGE with widely used four similarity measurements including Leacock
and Chodorow. We conducted two kinds of evaluations: first is calculation of similarity using the
varied edge-weighting and second is for the discriminative capability using conceptual distances between
comparative concepts. To verify the superiority of SSINEGE, we compared the calculated
similarities of SSINEGE with Leacock and Chodorow. As the results, we verified that the calculated
similarity of SSINEGE is significantly increased than the other comparatives.