Searched for: subject%3A%22Community%255C%2Bdetection%22
(1 - 13 of 13)
document
Wang, Beichen (author)
Community detection and graph partitioning have seamlessly integrated themselves into the fabric of network science by providing valuable insights into the structure, function, and dynamics of complex networks. In this thesis, a comprehensive performance comparison of the recently introduced Linear Clustering Process (LCP) is carried out against...
master thesis 2023
document
Freeman, Alexander (author)
Inductive logic programming is a technique that generates logic programs which keep to a given specification using a background knowledge. We propose a new task in the field of pro- gram synthesis called Time-gated Partition-selection Inductive Logic Programming, consisting of splitting the background knowledge into partitions and selecting only...
master thesis 2023
document
Theunisz, Jurriën (author)
Single-cell RNA sequencing data clustering is a valuable technique for demonstrating cell-to-cell heterogeneity and revealing cell dynamics within and amongst groups. Large up-scaling of scRNA-seq datasets in recent years pose computational challenges for existing state-of-the-art clustering techniques. A possible solution to tackle these...
bachelor thesis 2023
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Stein, Jonas (author), Ott, Dominik (author), Nüßlein, Jonas (author), Bucher, David (author), Schönfeld, Mirco (author), Feld, S. (author)
The analysis of network structure is essential to many scientific areas ranging from biology to sociology. As the computational task of clustering these networks into partitions, i.e., solving the community detection problem, is generally NP-hard, heuristic solutions are indispensable. The exploration of expedient heuristics has led to the...
journal article 2023
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Fernández Robledo, O. (author), Klepper, M. (author), van Boven, E.F.M. (author), Wang, H. (author)
Community detection of temporal (time-evolving) bipartite networks is challenging because it can be performed either on the temporal bipartite network, or on various projected networks, composed of only one type of nodes, via diverse community detection algorithms. In this paper, we aim to systematically design detection methods addressing...
conference paper 2023
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Segovia Castillo, P. (author), Puig, Vicenç (author), Duviella, Eric (author)
This work is concerned with the design of a two-step distributed state estimation scheme for large-scale systems in the presence of unknown-but-bounded disturbances and noise. The set-membership approach is employed to construct a compact set containing the states consistent with system measurements and bounded noise and disturbances. The...
journal article 2022
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Brandirali, Tommaso (author)
Large software systems today require increasingly complex models of their execution to aid the analysis of their behavior. Such execution models are impractical to compile by hand, and current approaches to their automated generation are either not generalizable or not scalable enough. This paper addresses this problem with a new approach based...
bachelor thesis 2021
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Wang, Z. (author), Luo, D. (author), Cats, O. (author), Verma, T. (author)
Hierarchy is regarded as a natural phenomenon of public transport networks (PTN). The imbalanced distribution of passenger flow result in a hierarchical structure of PTN and it is also related to the development of technology and the introduction of new modes. However, there is still a lack of knowledge on how to identify the hierarchical...
conference paper 2020
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Yap, M.D. (author), Luo, D. (author), Cats, O. (author), van Oort, N. (author), Hoogendoorn, S.P. (author)
Minimizing passenger transfer times through public transport (PT) transfer synchronization is important during tactical planning and real-time control. However, there are computational challenges for solving this Timetable Synchronization Problem (TSP) for large, real-world urban PT networks. Hence, in this study we propose a data-driven,...
journal article 2019
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Jiang, Xuehan (author)
Information systems, such as information retrieval machines and recommendation systems, utilize various user information and history behaviors to provide personalized content to users. However, a debate on whether the personalization in information systems can trigger the online echo chamber effect has emerged. The online echo chamber effect...
master thesis 2018
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Zhang, H. (author), Peng, Minfang (author), Palensky, P. (author)
Complex network theory is introduced to solve the islanding problem in an emergency of distribution networks. In this study, the authors put forward an intentional islanding method based on community detection. In this method, a new index has been defined called electrical edge betweenness, on the strength of edge betweenness in complex networks...
journal article 2018
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Huang, H. (author)
Complex networks are a special type of graph that frequently appears in nature and in many different fields of science and engineering. Studying complex networks is the key to solve the problems in these fields. Complex networks have unique features which we cannot find in regular graphs, and the study of complex networks gives rise to many...
master thesis 2015
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Blenn, N. (author), Doerr, C. (author), Van Kester, B. (author), Van Mieghem, P. (author)
As Online Social Networks (OSNs) become an intensive sub- ject of research for example in computer science, networking, social sci- ences etc., a growing need for valid and useful datasets is present. The time taken to crawl the network is however introducing a bias which should be minimized. Usual ways of addressing this problem are sampling...
conference paper
Searched for: subject%3A%22Community%255C%2Bdetection%22
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