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Measuring semantic relatedness based on ontology

Authors: null Lin Zhang; null Xiaojie Zheng; null Jie Hu;

Measuring semantic relatedness based on ontology

Abstract

The need of determining the degree of semantic similarity/relatedness between two concepts within ontology is becoming an increasingly important task in the field of Information Retrieval. Semantic similarity is only a special case of semantic relatedness. Although a great attention has been paid to design semantic similarity methods based on ontology, there has been little discussion about the methods of semantic relatedness methods. In this paper, based on distance-based calculation model to calculate concepts' similarity within ontology, we introduced an improved method for measuring semantic relatedness. In addition, our approach considers some important properties such as concepts' depth, density, relation distance to measure semantic similarity/relatedness. The experimental studies are provided to illustrate that our approach is reasonable.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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