Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/88913
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Land Surveying and Geo-Informatics | - |
dc.creator | Xu, QX | - |
dc.creator | Shi, WZ | - |
dc.date.accessioned | 2021-01-11T02:42:28Z | - |
dc.date.available | 2021-01-11T02:42:28Z | - |
dc.identifier.issn | 1682-1750 | - |
dc.identifier.uri | http://hdl.handle.net/10397/88913 | - |
dc.description | 22nd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing, Aug 25-Sep 01, 2012, Melbourne, Australia | en_US |
dc.language.iso | en | en_US |
dc.publisher | International Congress for Photogrammetry and Remote Sensing | en_US |
dc.rights | © Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 License (https://creativecommons.org/licenses/by/3.0/). | en_US |
dc.rights | The following publication Xu, Q. X. and Shi, W. Z.: A COMPARISON OF SEMANTIC SIMILARITY MODELS IN EVALUATING CONCEPT SIMILARITY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B2, 173–178, 2012 is available at https://dx.doi.org/10.5194/isprsarchives-XXXIX-B2-173-2012 | en_US |
dc.subject | Semantic similarity | en_US |
dc.subject | Concept similarity | en_US |
dc.subject | Geometric model | en_US |
dc.subject | Feature model | en_US |
dc.subject | Network model | en_US |
dc.subject | Transformational model | en_US |
dc.title | A comparison of semantic similarity models in evaluating concept similarity | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 173 | - |
dc.identifier.epage | 178 | - |
dc.identifier.volume | XXXIX-B2 | - |
dc.identifier.doi | 10.5194/isprsarchives-XXXIX-B2-173-2012 | - |
dcterms.abstract | The semantic similarities are important in concept definition, recognition, categorization, interpretation, and integration. Many semantic similarity models have been established to evaluate semantic similarities of objects or/and concepts. To find out the suitability and performance of different models in evaluating concept similarities, we make a comparison of four main types of models in this paper: the geometric model, the feature model, the network model, and the transformational model. Fundamental principles and main characteristics of these models are introduced and compared firstly. Land use and land cover concepts of NLCD92 are employed as examples in the case study. The results demonstrate that correlations between these models are very high for a possible reason that all these models are designed to simulate the similarity judgement of human mind. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | International archives of the photogrammetry, remote sensing and spatial information sciences, 1 Aug. 2012, v. XXXIX-B2, p. 173-178 | - |
dcterms.isPartOf | International archives of the photogrammetry, remote sensing and spatial information sciences | - |
dcterms.issued | 2012-08-01 | - |
dc.identifier.isi | WOS:000358210100031 | - |
dc.relation.conference | Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing | - |
dc.identifier.eissn | 2194-9034 | - |
dc.description.validate | 202101 bcrc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Conference Paper |
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File | Description | Size | Format | |
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Xu_Semantic_Similarity_Models.pdf | 682.39 kB | Adobe PDF | View/Open |
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