An Enhanced Method to Compute the Similarity Between Concepts of Ontology (original) (raw)
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Computational models of semantic similarity can be found in many applications, with the aim to give this additional knowledge to reason about their data. The choice of a similarity measure is very crucial for a successful implementation of reasoning. In this work, we present an update of similarity calculation presented by Wu and Palmer which is considered the fastest in terms of generation time of similarity. The results show that the measure provides produced a marked improvement in the relevance of the values produced for the two concepts similarity in ontology.
A New Measure of the Calculation of Semantic Distance between Ontology Concepts
International Journal of Information Technology and Computer Science, 2015
Semantic similarity calculation models are found in many applications, with the aim to give additional knowledge to reason about their data. The choice of a similarity measure is quite crucial for a successful implementation of reasoning. In this work, we present an update of similarity calculation presented by Wu and Palmer which is considered the fastest in time generation of similarity. The results obtained show that the measure produced provides a significant improvement in the relevance of the values produced for the similarity of two concepts in ontology.
Similarity Identification and Measurement between Ontologies
The Journal of American Science, 2010
Abstract: The retrieval of relevant and precise information from web has always been remained a serious problem. To address this problem, the idea of ontologies-based web, so-called semantic web, was proposed in 2001. But the problem is not completely solved due to the semantic ...
A new approach for measuring semantic similarity of ontology concepts using dynamic programming
arXiv (Cornell University), 2021
Today, with the emergence of semantic web technologies and increasing of information quantity, searching for information based on the semantic web has become a fertile area of research. For this reason, a large number of studies are performed based on the measure of semantic similarity. Therefore, in this paper, we propose a new method of semantic similarity measuring which uses the dynamic programming to compute the semantic distance between any two concepts defined in the same hierarchy of ontology. Then, we base on this result to compute the semantic similarity. Finally, we present an experimental comparison between our method and other methods of similarity measuring.
Comparison of ontology-based semantic-similarity measures
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2008
Semantic-similarity measures quantify concept similarities in a given ontology. Potential applications for these measures include search, data mining, and knowledge discovery in database or decision-support systems that utilize ontologies. To date, there have not been comparisons of the different semantic-similarity approaches on a single ontology. Such a comparison can offer insight on the validity of different approaches. We compared 3 approaches to semantic similarity-metrics (which rely on expert opinion, ontologies only, and information content) with 4 metrics applied to SNOMED-CT. We found that there was poor agreement among those metrics based on information content with the ontology only metric. The metric based only on the ontology structure correlated most with expert opinion. Our results suggest that metrics based on the ontology only may be preferable to information-content-based metrics, and point to the need for more research on validating the different approaches.
Assessing Similarity Between Ontologies : The Case of the Conceptual Similarity
International journal of Web & Semantic Technology
In ontology engineering, there are many cases where assessing similarity between ontologies is required, this is the case of the alignment activities, ontology evolutions, ontology similarities, etc. This paper presents a new method for assessing similarity between concepts of ontologies. The method is based on the set theory, edges and feature similarity. We first determine the set of concepts that is shared by two ontologies and the sets of concepts that are different from them. Then, we evaluate the average value of similarity for each set by using edges-based semantic similarity. Finally, we compute similarity between ontologies by using average values of each set and by using feature-based similarity measure too.
Similarity Measure Based On Edge Counting Using Ontology
2012
Building the ontology from the scratch is a difficult process and there is no proper fully automated ontology construction methodology is available. But more and more ontologies are created and available in the web, reusing the existing ontology is reasonable for the ontology developers. Ontology reuse is one of the research issue which leads to ontology mapping, ontology merging and ontology integration. Ontology mapping process required to find the semantic similarity between the terms. Semantic similarity can be identified by calculating lexical similarity and conceptual similarity. Wu and Palmer developed a simple and good performance algorithm compared to other similarity measure measures. In this paper, a modified algorithm of Wu and Palmer is discussed and the results are compared with Wu and Palmer algorithm.
Conceptual Similarity Measurement Algorithm For Domain Specific Ontology
International Journal of Information Technology, Modeling and Computing, 2014
This paper presents the similarity measurement algorithm for domain specific terms collected in the ontology based data integration system. This similarity measurement algorithm can be used in ontology mapping and query service of ontology based data integration system. In this paper, we focus on the web query service to apply this proposed algorithm. Concepts similarity is important for web query service because the words in user input query are not same wholly with the concepts in ontology. So, we need to extract the possible concepts that are match or related to the input words with the help of machine readable dictionary WordNet. Sometimes, we use the generated mapping rules in query generation procedure for some words that cannot be confirmed the similarity of these words by WordNet. We prove the effect of this algorithm with two degree semantic result of web mining by generating the concepts results obtained form the input query.
2006
Semantic Similarity relates to computing the similarity between concepts (terms) which are not necessarily lexically similar. We investigate approaches to computing semantic similarity by mapping terms to an ontology and by examining their relationships in that ontology. More specifically, we investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). The most popular semantic similarity methods are implemented and evaluated using WordNet and MeSH. The focus of this work is also on cross ontology methods which are capable of computing the semantic similarity between terms stemming from different ontologies (WordNet and MeSH in this work). This is a far more difficult problem (than the single ontology one referred to above) which has not been investigated adequately in the literature. X-Similarity, a novel cross-ontology similarity method is also a contribution of this work. All methods examined in this work are integrated into a semantic similarity system which is accessible on the Web.
A Layered Approach for Similarity Measurement Between Ontologies
Journal of American Science, 2010
Abstract: With the vision of Semantic Web, the ontology operations such as aligning, merging and mapping have gained much importance. The measuring of similarity between concepts of source ontologies is preprocessing of all these operations. Several techniques have been ...