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You searched for subject:(Overlapping clusters). Showing records 1 – 3 of 3 total matches.

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University of Texas – Austin

1. Whang, Joyce Jiyoung. Overlapping community detection in massive social networks.

Degree: Computer Sciences, 2015, University of Texas – Austin

Massive social networks have become increasingly popular in recent years. Community detection is one of the most important techniques for the analysis of such complex networks. A community is a set of cohesive vertices that has more connections inside the set than outside. In many social and information networks, these communities naturally overlap. For instance, in a social network, each vertex in a graph corresponds to an individual who usually participates in multiple communities. In this thesis, we propose scalable overlapping community detection algorithms that effectively identify high quality overlapping communities in various real-world networks. We first develop an efficient overlapping community detection algorithm using a seed set expansion approach. The key idea of this algorithm is to find good seeds and then greedily expand these seeds using a personalized PageRank clustering scheme. Experimental results show that our algorithm significantly outperforms other state-of-the-art overlapping community detection methods in terms of run time, cohesiveness of communities, and ground-truth accuracy. To develop more principled methods, we formulate the overlapping community detection problem as a non-exhaustive, overlapping graph clustering problem where clusters are allowed to overlap with each other, and some nodes are allowed to be outside of any cluster. To tackle this non-exhaustive, overlapping clustering problem, we propose a simple and intuitive objective function that captures the issues of overlap and non-exhaustiveness in a unified manner. To optimize the objective, we develop not only fast iterative algorithms but also more sophisticated algorithms using a low-rank semidefinite programming technique. Our experimental results show that the new objective and the algorithms are effective in finding ground-truth clusterings that have varied overlap and non-exhaustiveness. We extend our non-exhaustive, overlapping clustering techniques to co-clustering where the goal is to simultaneously identify a clustering of the rows as well as the columns of a data matrix. As an example application, consider recommender systems where users have ratings on items. This can be represented by a bipartite graph where users and items are denoted by two different types of nodes, and the ratings are denoted by weighted edges between the users and the items. In this case, co-clustering would be a simultaneous clustering of users and items. We propose a new co-clustering objective function and an efficient co-clustering algorithm that is able to identify overlapping clusters as well as outliers on both types of the nodes in the bipartite graph. We show that our co-clustering algorithm is able to effectively capture the underlying co-clustering structure of the data, which results in boosting the performance of a standard one-dimensional clustering. Finally, we study the design of parallel data-driven algorithms, which enables us to further increase the scalability of our overlapping community detection algorithms. Using… Advisors/Committee Members: Dhillon, Inderjit S. (advisor), Grauman, Kristen (committee member), Mooney, Raymond J (committee member), Pingali, Keshav (committee member), Gleich, David F (committee member).

Subjects/Keywords: Community detection; Clustering; Social networks; Overlapping communities; Overlapping clusters; Non-exhaustive clustering; Seed expansion; K-means; Semidefinite programming; Co-clustering; PageRank; Data-driven algorithm; Scalable computing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Whang, J. J. (2015). Overlapping community detection in massive social networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33272

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Whang, Joyce Jiyoung. “Overlapping community detection in massive social networks.” 2015. Thesis, University of Texas – Austin. Accessed June 16, 2019. http://hdl.handle.net/2152/33272.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Whang, Joyce Jiyoung. “Overlapping community detection in massive social networks.” 2015. Web. 16 Jun 2019.

Vancouver:

Whang JJ. Overlapping community detection in massive social networks. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/2152/33272.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Whang JJ. Overlapping community detection in massive social networks. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33272

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Beka, Sylvia. The Genomics of Type 1 Diabetes Susceptibility Regions and Effect of Regulatory SNPs .

Degree: 2016, University of Hertfordshire

Human complex diseases, like Diabetes and Cancer, affect many people worldwide today. Despite existing knowledge, many of these diseases are still not preventable. Complex diseases are known to be caused by a combination of genetic factors, as well as environmental and life style factors. The scope of this investigation covered the genomics of Type 1 Diabetes (T1D). There are 49 human genomic regions that are known to carry markers (disease-associated single nucleotide mutations) for T1D, and these were extensively studied in this research. The aim was to find out in how far this disease may be caused by problems in gene regulation rather than in gene coding. For this, the genetic factors associated with T1D, including the single point mutations and susceptibility regions, were characterised on the basis of their genomic attributes. Furthermore, mutations that occur in binding sites for transcription factors were analysed for change in the conspicuousness of their binding region, caused by allele substitution. This is called SNP (Single nucleotide polymorphism) sensitivity. From this study, it was found that the markers for T1D are mostly non-coding SNPs that occur in introns and non-coding gene transcripts, these are structures known to be involved in gene regulatory activity. It was also discovered that the T1D susceptibility regions contain an abundance of intronic, non-coding transcript and regulatory nucleotides, and that they can be split into three distinct groups on the basis of their structural and functional genomic contents. Finally, using an algorithm designed for this study, thirty-seven SNPs that change the representation of their surrounding region were identified. These regulatory mutations are non-associated T1D-SNPs that are mostly characterised by Cytosine to Thymine (C-T) transition mutations. They were found to be closer in average distance to the disease-associated SNPs than other SNPs in binding sites, and also to occur frequently in the binding motifs for the USF (Upstream stimulatory factor) protein family which is linked to problems in Type 2 diabetes.

Subjects/Keywords: SNPs; Polymorphisms; Type 1 Diabetes; Complex disease; DNA; Sequences; Susceptibility; Region; Regulatory; Sensitivity; Functional; Transcription factor; Transcription; Binding; TFBS; Reference allele; Mutant allele; Gene; Transcript; Protein-coding; Non-coding; RNA transcript; Overlapping; Expression; Cluster analysis; Representation; Binding signal; Motif change; Profile; Complex disease; Genome; Genetic factor; Ensemble; VEP; T1Dbase; Ravendbase; Clusters; Profiles; Features; Structural; Mutation; Associated; Non-associated

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Beka, S. (2016). The Genomics of Type 1 Diabetes Susceptibility Regions and Effect of Regulatory SNPs . (Thesis). University of Hertfordshire. Retrieved from http://hdl.handle.net/2299/17200

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Beka, Sylvia. “The Genomics of Type 1 Diabetes Susceptibility Regions and Effect of Regulatory SNPs .” 2016. Thesis, University of Hertfordshire. Accessed June 16, 2019. http://hdl.handle.net/2299/17200.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Beka, Sylvia. “The Genomics of Type 1 Diabetes Susceptibility Regions and Effect of Regulatory SNPs .” 2016. Web. 16 Jun 2019.

Vancouver:

Beka S. The Genomics of Type 1 Diabetes Susceptibility Regions and Effect of Regulatory SNPs . [Internet] [Thesis]. University of Hertfordshire; 2016. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/2299/17200.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Beka S. The Genomics of Type 1 Diabetes Susceptibility Regions and Effect of Regulatory SNPs . [Thesis]. University of Hertfordshire; 2016. Available from: http://hdl.handle.net/2299/17200

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Αθανασάκη, Μαρία. Παραλληλοποίηση κώδικα βρόχων σε αρχιτεκτονικές μη ομοιόμορφης προσπέλασης μνήμης (NUMA).

Degree: 2005, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ)

Subjects/Keywords: Μετασχηματισμός tiling; Μετασχηματισμός υπερκόμβων; Ομαδοποίηση υπερκόμβων; Αλληλοεπικάλυψη επικοινωνίας και υπολογισμών; Υπερεπίπεδα; Συστοιχίες πολυεπεξεργαστικών μονάδων; Περιορισμένος αριθμός κόμβων; Supernodes; Loop tiling; Overlapping communication; Pipelined schedules; Hyperplanes; Clusters of SMPs; Fixed numbers of nodes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Αθανασάκη, . . (2005). Παραλληλοποίηση κώδικα βρόχων σε αρχιτεκτονικές μη ομοιόμορφης προσπέλασης μνήμης (NUMA). (Thesis). National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Retrieved from http://hdl.handle.net/10442/hedi/16269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Αθανασάκη, Μαρία. “Παραλληλοποίηση κώδικα βρόχων σε αρχιτεκτονικές μη ομοιόμορφης προσπέλασης μνήμης (NUMA).” 2005. Thesis, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Accessed June 16, 2019. http://hdl.handle.net/10442/hedi/16269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Αθανασάκη, Μαρία. “Παραλληλοποίηση κώδικα βρόχων σε αρχιτεκτονικές μη ομοιόμορφης προσπέλασης μνήμης (NUMA).” 2005. Web. 16 Jun 2019.

Vancouver:

Αθανασάκη . Παραλληλοποίηση κώδικα βρόχων σε αρχιτεκτονικές μη ομοιόμορφης προσπέλασης μνήμης (NUMA). [Internet] [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2005. [cited 2019 Jun 16]. Available from: http://hdl.handle.net/10442/hedi/16269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Αθανασάκη . Παραλληλοποίηση κώδικα βρόχων σε αρχιτεκτονικές μη ομοιόμορφης προσπέλασης μνήμης (NUMA). [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2005. Available from: http://hdl.handle.net/10442/hedi/16269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.