Ontology-based information content computation

Sánchez, David; Batet, Montserrat; Isern, David

doi:10.1016/j.knosys.2010.10.001

Cited by 233 publications

(127 citation statements)

References 27 publications

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“…We then use hierarchical clustering to obtain the hierarchies derived from the selected feature sets. In the next step, information content-based semantic similarity measures (Jiang and Conrath, 1997;Sánchez et al, 2011) are implemented to compute the pairwise similarity between each pair of classes in the derived as well as the original ontology hierarchy. The Mantel test (Mantel, 1967) is implemented to select the best representing feature set based on the correlation coe cient and p-value.…”

Section: Proposed Methodsmentioning

confidence: 99%

Spatiotemporal enabled Content-based Image Retrieval

Belgiu¹,

Sudmanns²,

Tiede³

et al. 2016

GIScience

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Wireless Sensor Networks (WSNs) are widely used for monitoring and observation of dynamic phenomena. A sensor in WSNs covers only a limited region, depending on its sensing and communicating ranges, as well as the environment configuration. For efficient deployment of sensors in a WSN the coverage estimation is a critical issue. Probabilistic methods are among the most accurate models proposed for sensor coverage estimation. However, most of these methods are based on raster representation of the environment for coverage estimation which limits their quality. In this paper, we propose a probabilistic method for estimation of the coverage of a sensor network based on 3D vector representation of the environment.

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Section: Proposed Methodsmentioning

confidence: 99%

Spatiotemporal enabled Content-based Image Retrieval

Belgiu¹,

Sudmanns²,

Tiede³

et al. 2016

GIScience

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“…[33]; most of these existing semantic similarity measures can be classified into one of these four main categories.…”

Section: Related Workmentioning

confidence: 99%

CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures

Martinez‐Gil¹

2017

Preprint

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Semantic similarity measurement aims to determine the likeness between two text expressions that use different lexicographies for representing the same real object or idea. There are a lot of semantic similarity measures for addressing this problem. However, the best results have been achieved when aggregating a number of simple similarity measures. This means that after the various similarity values have been calculated, the overall similarity for a pair of text expressions is computed using an aggregation function of these individual semantic similarity values. This aggregation is often computed by means of statistical functions. In this work, we present CoTO (Consensus or Trade-Off) a solution based on fuzzy logic that is able to outperform these traditional approaches.

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“…[27], most of existing semantic similarity measures can be classified into one of these four main categories:…”

Section: Related Workmentioning

confidence: 99%

“…Studying the co-occurrence of terms in a text corpus has been usually used as an evidence of semantic similarity in the scientific literature [6,27]. In this work, we propose adapting this paradigm for our purposes.…”

Section: Contributionmentioning

confidence: 99%

Analysis of word co-occurrence in human literature for supporting semantic correspondence discovery

Martinez‐Gil

Pichler

2014

Proceedings of the 14th International Conference on Knowledge Technologies and Data-Driven Business

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Semantic similarity measurement aims to determine the likeness between two text expressions that use different lexicographies for representing the same real object or idea. In this work, we describe the way to exploit broad cultural trends for identifying semantic similarity. This is possible through the quantitative analysis of a vast digital book collection representing the digested history of humanity. Our research work has revealed that appropriately analyzing the co-occurrence of words in some periods of human literature can help us to determine the semantic similarity between these words by means of computers with a high degree of accuracy.

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Ontology-based information content computation

Cited by 233 publications

References 27 publications

Spatiotemporal enabled Content-based Image Retrieval

Spatiotemporal enabled Content-based Image Retrieval

CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures

Analysis of word co-occurrence in human literature for supporting semantic correspondence discovery

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