Extended TvX: A New Method Feature Based Semantic Similarity for Multiple Ontology
2017
Semantic similarity between the terms is the main phase in information retrieval and information integration, which requires semantic content matching. Semantic similarity function is important in psychology, artificial intelligence and cognitive science. The problem of integrating various sources is the matching between ontological concepts. In this paper, we proposed to develop this method by analyzing the semantic similarity between the modeled taxonomical knowledge and features in different ontology. This paper contains a review on semantic similarity and multiple ontology that focuses on the feature-based approach. Besides that, we proposed a method, namely a semantic similarity that overcomes the limitation of different features of terms compared. As a result, we are able to develop a better method that improves the accuracy of the similarity measurement.
Keywords:
- Semantic integration
- Semantic similarity
- Semantic computing
- Ontology-based data integration
- Semantic technology
- Information retrieval
- Probabilistic latent semantic analysis
- Upper ontology
- Artificial intelligence
- Computer science
- Ontology Inference Layer
- Pattern recognition
- Natural language processing
- Ontology alignment
- Correction
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