Geographic Projection of Cluster Composites

Kleiweg, Peter; Nerbonne, John; Bosveld, Leonie

doi:10.1007/978-3-540-25931-2_48

Cited by 12 publications

(9 citation statements)

References 1 publication

(2 reference statements)

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“…To overcome this instability, two methods have been suggested and tested during the last years, 'noisy clustering' (Kleiweg et al, 2004) and 'bootstrapping' (Nerbonne et al, 2008). We applied noisy clustering to our dataset to obtain robust clustering results.…”

Section: Stable Clustering: Probabilistic Dendrograms and Mapsmentioning

confidence: 99%

Linguistic advergence and divergence in north-western Catalan: A dialectometric investigation of dialect leveling and border effects

Valls

Wieling

Nerbonne

2013

Literary and Linguistic Computing

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This paper investigates several linguistic changes which are ongoing in north-western Catalan using a contemporary corpus. We take advantage of a range of dialectometric methods that allow us to calculate and analyze the linguistic distance between varieties in apparent time from an aggregate perspective. Specifically, we pay attention to the process of structural dialect loss due to linguistic advergence to standard and eastern Catalan in many north-western Catalan dialects located in Catalonia (Spain) and Andorra. We also provide evidence that the dialect leveling taking place in these two areas strongly contrasts with the relative stability of the Catalan dialects on the other side of the Catalan-Aragonese border in Spain, where Catalan is not an official language. These opposite sociolinguistic situations (Catalonia and Andorra have strong language policies to support Catalan, whereas Aragon does not) have triggered a twofold process of vertical advergence between the Catalan spoken in Catalonia and Andorra towards the prestigious varieties, on the one hand; and of horizontal divergence between these dialects and those located in Aragon, on the other hand. This situation has notably strengthened the border differences between Aragon and Catalonia during the last 80 years. This paper is one of the first attempts to study the border effects not only between regions belonging to different countries, but also between different administrative regions within the same country. In addition, we investigate the different roles of urban versus rural areas, providing support for the view that the spatial and hierarchical diffusion patterns are complementary.

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Section: Stable Clustering: Probabilistic Dendrograms and Mapsmentioning

confidence: 99%

Linguistic advergence and divergence in north-western Catalan: A dialectometric investigation of dialect leveling and border effects

Valls

Wieling

Nerbonne

2013

Literary and Linguistic Computing

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“…This is illustrated with a 500-site data set from Bulgaria, where input matrices which correlate very highly (r = 0.97) still yield very different clusterings. Kleiweg et al (2004) introduce composite clustering, in which random noise is added to matrices during repeated clustering. The resulting borders are then projected onto the map.…”

mentioning

confidence: 99%

Projecting Dialect Distances to Geography: Bootstrap Clustering vs. Noisy Clustering

Nerbonne

Heeringa

Manni

et al. 2008

Data Analysis, Machine Learning and Applications

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Abstract. Dialectometry produces aggregate distance matrices in which a distance is specified for each pair of sites. By projecting groups obtained by clustering onto geography one compares results with traditional dialectology, which produced maps partitioned into implicitly non-overlapping dialect areas. The importance of dialect areas has been challenged by proponents of continua, but they too need to compare their findings to older literature, expressed in terms of areas.Simple clustering is unstable, meaning that small differences in the input matrix can lead to large differences in results (Jain et al. 1999). This is illustrated with a 500-site data set from Bulgaria, where input matrices which correlate very highly (r = 0.97) still yield very different clusterings. Kleiweg et al. (2004) introduce composite clustering, in which random noise is added to matrices during repeated clustering. The resulting borders are then projected onto the map.The present contribution compares Kleiweg et al.'s procedure to resampled bootstrapping, and also shows how the same procedure used to project borders from composite clustering may be used to project borders from bootstrapping.

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“…Furthermore the RMSD's for the unique conformations were calculated using the Kleiweg clustering method (Kleiweg et al, 2004) to perform the hierarchical cluster analysis. The clustering can be visually represented by constructing a dendrogram, which indicates the relationship between the items in the data set (i.e.…”

Section: Resultsmentioning

confidence: 99%

An Assessment of the Conformational Profile of Neuromedin B Using Different Computational Sampling Procedures

Sharma¹,

Singh²,

Bisetty³

et al. 2012

Molecular Dynamics - Studies of Synthetic and Biological Macromolecules

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Geographic Projection of Cluster Composites

Cited by 12 publications

References 1 publication

Linguistic advergence and divergence in north-western Catalan: A dialectometric investigation of dialect leveling and border effects

Linguistic advergence and divergence in north-western Catalan: A dialectometric investigation of dialect leveling and border effects

Projecting Dialect Distances to Geography: Bootstrap Clustering vs. Noisy Clustering

An Assessment of the Conformational Profile of Neuromedin B Using Different Computational Sampling Procedures

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