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description Publicationkeyboard_double_arrow_right Article 2015 United StatesPublisher:MDPI AG Funded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Ballatore, Andrea; Bertolotto, Michela; Wilson, David;Ballatore, Andrea; Bertolotto, Michela; Wilson, David;doi: 10.3390/ijgi4020471
Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web’s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS). This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects.
ISPRS International ... arrow_drop_down ISPRS International Journal of Geo-InformationOther literature type . Article . 2015 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2220-9964/4/2/471/pdfeScholarship - University of CaliforniaArticle . 2015Data sources: eScholarship - University of Californiaadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/ijgi4020471&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 18 citations 18 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert ISPRS International ... arrow_drop_down ISPRS International Journal of Geo-InformationOther literature type . Article . 2015 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2220-9964/4/2/471/pdfeScholarship - University of CaliforniaArticle . 2015Data sources: eScholarship - University of Californiaadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/ijgi4020471&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2014 IrelandPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer's semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity. Comment: GeoInformatica 2014
Maynooth University ... arrow_drop_down Maynooth University ePrints & eTheses ArchiveArticle . 2014 . Peer-reviewedData sources: Maynooth University ePrints & eTheses ArchivearXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2014License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10707-013-0197-8&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 41 citations 41 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!visibility 3visibility views 3 download downloads 156 Powered bymore_vert Maynooth University ... arrow_drop_down Maynooth University ePrints & eTheses ArchiveArticle . 2014 . Peer-reviewedData sources: Maynooth University ePrints & eTheses ArchivearXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2014License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10707-013-0197-8&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2013Publisher:Journal of Spatial Information Science Funded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE) as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach. Comment: Special feature on Semantic and Conceptual Issues in GIS (SeCoGIS)
Journal of Spatial I... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5311/josis.2013.7.128&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 5 citations 5 popularity Average influence Average impulse Average Powered by BIP!more_vert Journal of Spatial I... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5311/josis.2013.7.128&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Part of book or chapter of book 2012Publisher:Springer Berlin Heidelberg Funded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Andrea Ballatore; David C. Wilson; Michela Bertolotto;Andrea Ballatore; David C. Wilson; Michela Bertolotto;A cognitively plausible measure of semantic similarity between geographic concepts is valuable across several areas, including geographic information retrieval, data mining, and ontology alignment. Semantic similarity measures are not intrinsically right or wrong, but obtain a certain degree of cognitive plausibility in the context of a given application. A similarity measure can therefore be seen as a domain expert summoned to judge the similarity of a pair of concepts according to her subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we first define the similarity jury as a panel of experts having to reach a decision on the semantic similarity of a set of geographic concepts. Second, we have conducted an evaluation of 8 WordNet-based semantic similarity measures on a subset of OpenStreetMap geographic concepts. This empirical evidence indicates that a jury tends to perform better than individual experts, but the best expert often outperforms the jury. In some cases, the jury obtains higher cognitive plausibility than its best expert.
https://researchrepo... arrow_drop_down https://researchrepository.ucd...Part of book or chapter of bookLicense: CC BY NC NDData sources: UnpayWallhttps://doi.org/10.1007/978-3-...Part of book or chapter of book . 2012 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-642-33999-8_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu7 citations 7 popularity Average influence Average impulse Top 10% Powered by BIP!more_vert https://researchrepo... arrow_drop_down https://researchrepository.ucd...Part of book or chapter of bookLicense: CC BY NC NDData sources: UnpayWallhttps://doi.org/10.1007/978-3-...Part of book or chapter of book . 2012 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-642-33999-8_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
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description Publicationkeyboard_double_arrow_right Article 2015 United StatesPublisher:MDPI AG Funded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Ballatore, Andrea; Bertolotto, Michela; Wilson, David;Ballatore, Andrea; Bertolotto, Michela; Wilson, David;doi: 10.3390/ijgi4020471
Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web’s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS). This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects.
ISPRS International ... arrow_drop_down ISPRS International Journal of Geo-InformationOther literature type . Article . 2015 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2220-9964/4/2/471/pdfeScholarship - University of CaliforniaArticle . 2015Data sources: eScholarship - University of Californiaadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/ijgi4020471&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 18 citations 18 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert ISPRS International ... arrow_drop_down ISPRS International Journal of Geo-InformationOther literature type . Article . 2015 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2220-9964/4/2/471/pdfeScholarship - University of CaliforniaArticle . 2015Data sources: eScholarship - University of Californiaadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/ijgi4020471&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2014 IrelandPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer's semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity. Comment: GeoInformatica 2014
Maynooth University ... arrow_drop_down Maynooth University ePrints & eTheses ArchiveArticle . 2014 . Peer-reviewedData sources: Maynooth University ePrints & eTheses ArchivearXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2014License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10707-013-0197-8&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 41 citations 41 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!visibility 3visibility views 3 download downloads 156 Powered bymore_vert Maynooth University ... arrow_drop_down Maynooth University ePrints & eTheses ArchiveArticle . 2014 . Peer-reviewedData sources: Maynooth University ePrints & eTheses ArchivearXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2014License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10707-013-0197-8&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2013Publisher:Journal of Spatial Information Science Funded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.;Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE) as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach. Comment: Special feature on Semantic and Conceptual Issues in GIS (SeCoGIS)
Journal of Spatial I... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5311/josis.2013.7.128&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 5 citations 5 popularity Average influence Average impulse Average Powered by BIP!more_vert Journal of Spatial I... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2014Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5311/josis.2013.7.128&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Part of book or chapter of book 2012Publisher:Springer Berlin Heidelberg Funded by:SFI | SRC StratAG: Strategic Re...SFI| SRC StratAG: Strategic Research Cluster In Advanced GeotechnologiesAuthors: Andrea Ballatore; David C. Wilson; Michela Bertolotto;Andrea Ballatore; David C. Wilson; Michela Bertolotto;A cognitively plausible measure of semantic similarity between geographic concepts is valuable across several areas, including geographic information retrieval, data mining, and ontology alignment. Semantic similarity measures are not intrinsically right or wrong, but obtain a certain degree of cognitive plausibility in the context of a given application. A similarity measure can therefore be seen as a domain expert summoned to judge the similarity of a pair of concepts according to her subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we first define the similarity jury as a panel of experts having to reach a decision on the semantic similarity of a set of geographic concepts. Second, we have conducted an evaluation of 8 WordNet-based semantic similarity measures on a subset of OpenStreetMap geographic concepts. This empirical evidence indicates that a jury tends to perform better than individual experts, but the best expert often outperforms the jury. In some cases, the jury obtains higher cognitive plausibility than its best expert.
https://researchrepo... arrow_drop_down https://researchrepository.ucd...Part of book or chapter of bookLicense: CC BY NC NDData sources: UnpayWallhttps://doi.org/10.1007/978-3-...Part of book or chapter of book . 2012 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-642-33999-8_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu7 citations 7 popularity Average influence Average impulse Top 10% Powered by BIP!more_vert https://researchrepo... arrow_drop_down https://researchrepository.ucd...Part of book or chapter of bookLicense: CC BY NC NDData sources: UnpayWallhttps://doi.org/10.1007/978-3-...Part of book or chapter of book . 2012 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-642-33999-8_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu