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Simulating Developmental Changes in Noun Richness through Performance-limited Distributional Analysis
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Defaulting effects contribute to the simulation of cross-linguistic differences in Optional Infinitive errors
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Sinuosity and the affect grid: A method for adjusting repeated mood scores
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Cluster damage robustness analysis and space independent community detection in complex networks
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Gegov, Emil. - : Brunel University School of Engineering and Design PhD Theses, 2012
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Abstract:
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University. ; This thesis investigates the evolution of two very different complex systems using network theory. This multi-disciplinary technique is widely used to model and analyse vastly diverse systems of multiple interacting components, and therefore, it is applied in this thesis to study the complexity of the systems. This complexity is rooted in the components’ interactions such that the whole system is more than the sum of all the individual parts. The first novelty in this research is the proposal of a new type of structural perturbation, cluster damage, for measuring another dimension of network robustness. The second novelty is the first application of a community detection method, which uncovers space-independent communities in spatial networks, to airport and linguistic networks. A critical property of complex systems – robustness – is explored within a partial model of the Internet, by demonstrating a novel perturbation strategy based on the iterative removal of clusters. The main contribution of this theoretical case study is the methodology for cluster damage, which has not been investigated by literature on the robustness of complex networks. The model, part of the Internet at the Autonomous System level, only serves as a domain where the novel methodology is demonstrated, and it is chosen because the Internet is known to be robust due to its distributed (non-centralised) nature, even though it is often subjected to large perturbations and failures. The first applied case study is in the field of air transportation. Specifically, it explores the topology and passenger flows of the United States Airport Network (USAN) over two decades. The network model consists of a time-series of six network snapshots for the years 1990, 2000 and 2010, which capture bi-monthly passenger flows among US airports. Since the network is embedded in space, the volume of these flows is naturally affected by spatial proximity, and therefore, a model (recently proposed in the literature) accounting for this phenomenon is used to identify the communities of airports that have particularly high flows among them, given their spatial separation. The second applied case study – in the field of language acquisition – investigates the word co-occurrence network of children, as they develop their linguistic abilities at an early age. Similarly to the previous case study, the network model consists of six children and three discrete developmental stages. These networks are not embedded in physical space, but they are mapped to an artificial semantic space that defines the semantic distance between pairs of words. This novel approach allows for an additional dimension of network information that results in a more complete dataset. Then, community detection identifies groups of words that have particularly high co-occurrence frequency, given their semantic distance. This research highlights the fact that some general techniques from network theory, such as network modelling and analysis, can be successfully applied for the study of diverse systems, while others, such as community detection, need to be tailored for the specific system. However, methods originally developed for one domain may be applied somewhere completely new, as illustrated by the application of spatial community detection to a non-spatial network. This underlines the importance of inter-disciplinary research.
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Keyword:
Air transportation; Internet; Language acquisition
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URL: http://bura.brunel.ac.uk/handle/2438/7245
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| 5 |
Transition expertise: Cognitive factors and developmental processes that contribute to repeated successful career transitions amongst elite athletes, musicians and business people
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Modelling language acquisition in children using network theory
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In: European Perspectives on Cognitive Sciences (2011)
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Comparing MOSAIC and the variational learning model of the optional infinitive stage in early child language
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| 9 |
On the Utility of Conjoint and Compositional Frames and Utterance
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Simulating the referential properties of Dutch, German and English Root Infinitives in MOSAIC
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| 11 |
Does chess need intelligence? – A study with young chess players
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Modelling the developmental patterning of finiteness marking in English, Dutch, German and Spanish using MOSAIC
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Understanding the Developmental Dynamics of Subject Omission: The Role of Processing Limitations in Learning
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Simulating the Noun-Verb Asymmetry in the Productivity of Children’s Speech
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Linking working memory and long-term memory: A computational model of the learning of new words
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Jones, G; Gobet, F; Pine, J M. - : Blackwell Publishing. The definitive version is available at onlinelibrary.wiley.com, 2007
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Modelling the Development of Children’s use of Optional Infinitives in Dutch and English using MOSAIC
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Unifying cross-linguistic and within-language patterns of finiteness marking in MOSAIC
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On the resolution of ambiguities in the extraction of syntactic categories through chunking
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