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You searched for subject:(graph mining). Showing records 1 – 30 of 171 total matches.

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1. Μαλλιαρός, Φραγκίσκος. Δομική ανάλυση χρονικά εξελισσόμενων γραφημάτων : ιδιότητες, μοντέλα και εφαρμογές.

Degree: 2011, University of Patras

 Τα τελευταία χρόνια έχει παρατηρηθεί ιδιαίτερο ερευνητικό ενδιαφέρον στη μελέτη δικτύων (γραφημάτων) που προκύπτουν από διάφορες κοινωνικές, τεχνολογικές και επιστημονικές δραστηριότητες. Χαρακτηριστικά παραδείγματα αποτελούν το… (more)

Subjects/Keywords: Κοινωνικά δίκτυα; Ανθεκτικότητα; Ιδιότητες επέκτασης; Εξόρυξη γνώσης από δεδομένα γραφημάτων; 001.422 602 856 6; Social networks; Robustness; Expansion properties; Graph mining

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

APA (6th Edition):

Μαλλιαρός, . (2011). Δομική ανάλυση χρονικά εξελισσόμενων γραφημάτων : ιδιότητες, μοντέλα και εφαρμογές. (Masters Thesis). University of Patras. Retrieved from http://nemertes.lis.upatras.gr/jspui/handle/10889/4725

Chicago Manual of Style (16th Edition):

Μαλλιαρός, Φραγκίσκος. “Δομική ανάλυση χρονικά εξελισσόμενων γραφημάτων : ιδιότητες, μοντέλα και εφαρμογές.” 2011. Masters Thesis, University of Patras. Accessed April 07, 2020. http://nemertes.lis.upatras.gr/jspui/handle/10889/4725.

MLA Handbook (7th Edition):

Μαλλιαρός, Φραγκίσκος. “Δομική ανάλυση χρονικά εξελισσόμενων γραφημάτων : ιδιότητες, μοντέλα και εφαρμογές.” 2011. Web. 07 Apr 2020.

Vancouver:

Μαλλιαρός . Δομική ανάλυση χρονικά εξελισσόμενων γραφημάτων : ιδιότητες, μοντέλα και εφαρμογές. [Internet] [Masters thesis]. University of Patras; 2011. [cited 2020 Apr 07]. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/4725.

Council of Science Editors:

Μαλλιαρός . Δομική ανάλυση χρονικά εξελισσόμενων γραφημάτων : ιδιότητες, μοντέλα και εφαρμογές. [Masters Thesis]. University of Patras; 2011. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/4725


Aristotle University Of Thessaloniki (AUTH); Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης (ΑΠΘ)

2. Μωυσιάδης, Ελευθέριος. Αναγνώριση κοινοτήτων σε τόπους του παγκόσμιου ιστού.

Degree: 2009, Aristotle University Of Thessaloniki (AUTH); Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης (ΑΠΘ)

 Clustering is an important issue in the analysis and exploration of data. There is a wide area of clustering applications including information retrieval, image segmentation,… (more)

Subjects/Keywords: Ομαδοποίηση γράφων; Αναγνώριση κοινοτήτων; Τεχνητοί γράφοι ελέγχου; Λογοκλοπή; Παγκόσμιος ιστός; Τόπος παγκόσμιου ιστού; Graph clustering; Community mining; Benchmark graphs; Plagiarism; Web; Web site

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APA (6th Edition):

Μωυσιάδης, . . (2009). Αναγνώριση κοινοτήτων σε τόπους του παγκόσμιου ιστού. (Thesis). Aristotle University Of Thessaloniki (AUTH); Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης (ΑΠΘ). Retrieved from http://hdl.handle.net/10442/hedi/20556

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):

Μωυσιάδης, Ελευθέριος. “Αναγνώριση κοινοτήτων σε τόπους του παγκόσμιου ιστού.” 2009. Thesis, Aristotle University Of Thessaloniki (AUTH); Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης (ΑΠΘ). Accessed April 07, 2020. http://hdl.handle.net/10442/hedi/20556.

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

MLA Handbook (7th Edition):

Μωυσιάδης, Ελευθέριος. “Αναγνώριση κοινοτήτων σε τόπους του παγκόσμιου ιστού.” 2009. Web. 07 Apr 2020.

Vancouver:

Μωυσιάδης . Αναγνώριση κοινοτήτων σε τόπους του παγκόσμιου ιστού. [Internet] [Thesis]. Aristotle University Of Thessaloniki (AUTH); Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης (ΑΠΘ); 2009. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10442/hedi/20556.

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

Council of Science Editors:

Μωυσιάδης . Αναγνώριση κοινοτήτων σε τόπους του παγκόσμιου ιστού. [Thesis]. Aristotle University Of Thessaloniki (AUTH); Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης (ΑΠΘ); 2009. Available from: http://hdl.handle.net/10442/hedi/20556

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

3. 鈴木, 大輔. データマイニングを用いた量子計算データからの二元合金の物性予測.

Degree: Japan Advanced Institute of Science and Technology / 北陸先端科学技術大学院大学

Supervisor:Dam Hieu Chi

知識科学研究科

修士

Subjects/Keywords: data mining; quantum calculation; LASSO; graph

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APA (6th Edition):

鈴木, . (n.d.). データマイニングを用いた量子計算データからの二元合金の物性予測. (Thesis). Japan Advanced Institute of Science and Technology / 北陸先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10119/11994

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

鈴木, 大輔. “データマイニングを用いた量子計算データからの二元合金の物性予測.” Thesis, Japan Advanced Institute of Science and Technology / 北陸先端科学技術大学院大学. Accessed April 07, 2020. http://hdl.handle.net/10119/11994.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

鈴木, 大輔. “データマイニングを用いた量子計算データからの二元合金の物性予測.” Web. 07 Apr 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

鈴木 . データマイニングを用いた量子計算データからの二元合金の物性予測. [Internet] [Thesis]. Japan Advanced Institute of Science and Technology / 北陸先端科学技術大学院大学; [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10119/11994.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

鈴木 . データマイニングを用いた量子計算データからの二元合金の物性予測. [Thesis]. Japan Advanced Institute of Science and Technology / 北陸先端科学技術大学院大学; Available from: http://hdl.handle.net/10119/11994

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


University of Houston

4. -2977-8778. Machine Learning to Analyze fMRI Brain Activity Recordings.

Degree: PhD, Mathematics, 2019, University of Houston

 In recent years, data-driven machine learning (ML) algorithms have seen increased use to study brain activity fMRI time series. Giving mathematical solutions by constructing quantitative… (more)

Subjects/Keywords: Time Series Classification; Deep learning; Machine learning; Mutual Information; Functional magnetic resonance imaging (fMRI); Epilepsy Seizure Focus; Graph Mining

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APA (6th Edition):

-2977-8778. (2019). Machine Learning to Analyze fMRI Brain Activity Recordings. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/4661

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-2977-8778. “Machine Learning to Analyze fMRI Brain Activity Recordings.” 2019. Doctoral Dissertation, University of Houston. Accessed April 07, 2020. http://hdl.handle.net/10657/4661.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-2977-8778. “Machine Learning to Analyze fMRI Brain Activity Recordings.” 2019. Web. 07 Apr 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-2977-8778. Machine Learning to Analyze fMRI Brain Activity Recordings. [Internet] [Doctoral dissertation]. University of Houston; 2019. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10657/4661.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-2977-8778. Machine Learning to Analyze fMRI Brain Activity Recordings. [Doctoral Dissertation]. University of Houston; 2019. Available from: http://hdl.handle.net/10657/4661

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Missouri University of Science and Technology

5. Abedijaberi, Armita. Mining and analysis of real-world graphs.

Degree: PhD, Computer Science, Missouri University of Science and Technology

  "Networked systems are everywhere - such as the Internet, social networks, biological networks, transportation networks, power grid networks, etc. They can be very large… (more)

Subjects/Keywords: Graph; Large-Scale; Mining; Motif; Network; Robustness; Computer Sciences

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APA (6th Edition):

Abedijaberi, A. (n.d.). Mining and analysis of real-world graphs. (Doctoral Dissertation). Missouri University of Science and Technology. Retrieved from https://scholarsmine.mst.edu/doctoral_dissertations/2697

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Chicago Manual of Style (16th Edition):

Abedijaberi, Armita. “Mining and analysis of real-world graphs.” Doctoral Dissertation, Missouri University of Science and Technology. Accessed April 07, 2020. https://scholarsmine.mst.edu/doctoral_dissertations/2697.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

MLA Handbook (7th Edition):

Abedijaberi, Armita. “Mining and analysis of real-world graphs.” Web. 07 Apr 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Abedijaberi A. Mining and analysis of real-world graphs. [Internet] [Doctoral dissertation]. Missouri University of Science and Technology; [cited 2020 Apr 07]. Available from: https://scholarsmine.mst.edu/doctoral_dissertations/2697.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Council of Science Editors:

Abedijaberi A. Mining and analysis of real-world graphs. [Doctoral Dissertation]. Missouri University of Science and Technology; Available from: https://scholarsmine.mst.edu/doctoral_dissertations/2697

Note: this citation may be lacking information needed for this citation format:
No year of publication.


Georgia Tech

6. Agarwal, Virat. Algorithm design on multicore processors for massive-data analysis.

Degree: PhD, Computational Science and Engineering, 2010, Georgia Tech

 Analyzing massive-data sets and streams is computationally very challenging. Data sets in systems biology, network analysis and security use network abstraction to construct large-scale graphs.… (more)

Subjects/Keywords: Graph algorithms; Parallel computing; Massive data; Financial market data; Streaming data; Keyword scanning; Data mining; Algorithms; Pattern recognition systems; Computer algorithms

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APA (6th Edition):

Agarwal, V. (2010). Algorithm design on multicore processors for massive-data analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/34839

Chicago Manual of Style (16th Edition):

Agarwal, Virat. “Algorithm design on multicore processors for massive-data analysis.” 2010. Doctoral Dissertation, Georgia Tech. Accessed April 07, 2020. http://hdl.handle.net/1853/34839.

MLA Handbook (7th Edition):

Agarwal, Virat. “Algorithm design on multicore processors for massive-data analysis.” 2010. Web. 07 Apr 2020.

Vancouver:

Agarwal V. Algorithm design on multicore processors for massive-data analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/1853/34839.

Council of Science Editors:

Agarwal V. Algorithm design on multicore processors for massive-data analysis. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/34839


Purdue University

7. Ahmed, Nesreen Kamel. Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery.

Degree: PhD, Computer Science, 2015, Purdue University

 Network analysis and graph mining play a prominent role in providing insights and studying phenomena across various domains, including social, behavioral, biological, transportation, communication, and… (more)

Subjects/Keywords: Data Mining; Graph Mining; Machine Learning; Network Science; Sampling; Statistical Estimation

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APA (6th Edition):

Ahmed, N. K. (2015). Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery. (Doctoral Dissertation). Purdue University. Retrieved from https://docs.lib.purdue.edu/open_access_dissertations/1445

Chicago Manual of Style (16th Edition):

Ahmed, Nesreen Kamel. “Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery.” 2015. Doctoral Dissertation, Purdue University. Accessed April 07, 2020. https://docs.lib.purdue.edu/open_access_dissertations/1445.

MLA Handbook (7th Edition):

Ahmed, Nesreen Kamel. “Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery.” 2015. Web. 07 Apr 2020.

Vancouver:

Ahmed NK. Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery. [Internet] [Doctoral dissertation]. Purdue University; 2015. [cited 2020 Apr 07]. Available from: https://docs.lib.purdue.edu/open_access_dissertations/1445.

Council of Science Editors:

Ahmed NK. Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery. [Doctoral Dissertation]. Purdue University; 2015. Available from: https://docs.lib.purdue.edu/open_access_dissertations/1445

8. Ailem, Melissa. Sparsity-sensitive diagonal co-clustering algorithms for the effective handling of text data : Algorithmes d'optimisation du processus d'allocation de ressources pour l'infrastructure en tant que service en informatique en nuage.

Degree: Docteur es, Science de données, 2016, Sorbonne Paris Cité

 Dans le contexte actuel, il y a un besoin évident de techniques de fouille de textes pour analyser l'énorme quantité de documents textuelles non structurées… (more)

Subjects/Keywords: Classification croisée; Modularité de graphes; Modèles de mélanges; Fouille de textes; Matrices creuses; Données textuelles; Matrices document-terme; Co-clustering; Graph modularity; Mixture models; Text mining; Sparse data; Text data; Document-term matrices; Model-based co-clustering; 004.678

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APA (6th Edition):

Ailem, M. (2016). Sparsity-sensitive diagonal co-clustering algorithms for the effective handling of text data : Algorithmes d'optimisation du processus d'allocation de ressources pour l'infrastructure en tant que service en informatique en nuage. (Doctoral Dissertation). Sorbonne Paris Cité. Retrieved from http://www.theses.fr/2016USPCB087

Chicago Manual of Style (16th Edition):

Ailem, Melissa. “Sparsity-sensitive diagonal co-clustering algorithms for the effective handling of text data : Algorithmes d'optimisation du processus d'allocation de ressources pour l'infrastructure en tant que service en informatique en nuage.” 2016. Doctoral Dissertation, Sorbonne Paris Cité. Accessed April 07, 2020. http://www.theses.fr/2016USPCB087.

MLA Handbook (7th Edition):

Ailem, Melissa. “Sparsity-sensitive diagonal co-clustering algorithms for the effective handling of text data : Algorithmes d'optimisation du processus d'allocation de ressources pour l'infrastructure en tant que service en informatique en nuage.” 2016. Web. 07 Apr 2020.

Vancouver:

Ailem M. Sparsity-sensitive diagonal co-clustering algorithms for the effective handling of text data : Algorithmes d'optimisation du processus d'allocation de ressources pour l'infrastructure en tant que service en informatique en nuage. [Internet] [Doctoral dissertation]. Sorbonne Paris Cité; 2016. [cited 2020 Apr 07]. Available from: http://www.theses.fr/2016USPCB087.

Council of Science Editors:

Ailem M. Sparsity-sensitive diagonal co-clustering algorithms for the effective handling of text data : Algorithmes d'optimisation du processus d'allocation de ressources pour l'infrastructure en tant que service en informatique en nuage. [Doctoral Dissertation]. Sorbonne Paris Cité; 2016. Available from: http://www.theses.fr/2016USPCB087


Missouri University of Science and Technology

9. Alobaidi, Isam Abdulmunem. Predictive analysis of real-time strategy games using graph mining.

Degree: PhD, Computer Science, Missouri University of Science and Technology

 "Machine learning and computational intelligence have facilitated the development of recommendation systems for a broad range of domains. Such recommendations are based on contextual information… (more)

Subjects/Keywords: Data mining; Graph mining; Graph partitioning; Hotspot; Predictive analytics; Recommendation systems; Computer Sciences

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APA (6th Edition):

Alobaidi, I. A. (n.d.). Predictive analysis of real-time strategy games using graph mining. (Doctoral Dissertation). Missouri University of Science and Technology. Retrieved from https://scholarsmine.mst.edu/doctoral_dissertations/2824

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Chicago Manual of Style (16th Edition):

Alobaidi, Isam Abdulmunem. “Predictive analysis of real-time strategy games using graph mining.” Doctoral Dissertation, Missouri University of Science and Technology. Accessed April 07, 2020. https://scholarsmine.mst.edu/doctoral_dissertations/2824.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

MLA Handbook (7th Edition):

Alobaidi, Isam Abdulmunem. “Predictive analysis of real-time strategy games using graph mining.” Web. 07 Apr 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Alobaidi IA. Predictive analysis of real-time strategy games using graph mining. [Internet] [Doctoral dissertation]. Missouri University of Science and Technology; [cited 2020 Apr 07]. Available from: https://scholarsmine.mst.edu/doctoral_dissertations/2824.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Council of Science Editors:

Alobaidi IA. Predictive analysis of real-time strategy games using graph mining. [Doctoral Dissertation]. Missouri University of Science and Technology; Available from: https://scholarsmine.mst.edu/doctoral_dissertations/2824

Note: this citation may be lacking information needed for this citation format:
No year of publication.

10. Appel, Ana Paula. Métodos para o pré-processamento e mineração de grandes volumes de dados multidimensionais e redes complexas.

Degree: PhD, Ciências de Computação e Matemática Computacional, 2010, University of São Paulo

A mineração de dados é um processo computacionalmente caro, que se apoia no pré-processamento dos dados para aumentar a sua eficiência. As técnicas de redução… (more)

Subjects/Keywords: Amostragem balanceada; Banco de dados; Biased sampling; Database; Graph mining; Mineração de grafos

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APA (6th Edition):

Appel, A. P. (2010). Métodos para o pré-processamento e mineração de grandes volumes de dados multidimensionais e redes complexas. (Doctoral Dissertation). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13072010-101429/ ;

Chicago Manual of Style (16th Edition):

Appel, Ana Paula. “Métodos para o pré-processamento e mineração de grandes volumes de dados multidimensionais e redes complexas.” 2010. Doctoral Dissertation, University of São Paulo. Accessed April 07, 2020. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13072010-101429/ ;.

MLA Handbook (7th Edition):

Appel, Ana Paula. “Métodos para o pré-processamento e mineração de grandes volumes de dados multidimensionais e redes complexas.” 2010. Web. 07 Apr 2020.

Vancouver:

Appel AP. Métodos para o pré-processamento e mineração de grandes volumes de dados multidimensionais e redes complexas. [Internet] [Doctoral dissertation]. University of São Paulo; 2010. [cited 2020 Apr 07]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13072010-101429/ ;.

Council of Science Editors:

Appel AP. Métodos para o pré-processamento e mineração de grandes volumes de dados multidimensionais e redes complexas. [Doctoral Dissertation]. University of São Paulo; 2010. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13072010-101429/ ;

11. Aridhi, Sabeur. Distributed frequent subgraph mining in the cloud : Fouille de sous-graphes fréquents dans les nuages.

Degree: Docteur es, Informatique, 2013, Université Blaise-Pascale, Clermont-Ferrand II

Durant ces dernières années, l’utilisation de graphes a fait l’objet de nombreux travaux, notamment en bases de données, apprentissage automatique, bioinformatique et en analyse des… (more)

Subjects/Keywords: Fouille de sous-graphes; Partitionnement de graphes; Densité de graphe; MapReduce; Informatique dans les nuages; Modèles de coûts; Frequent subgraph mining; Graph partitioning; Graph density; MapReduce; Cloud computing; Cost models

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APA (6th Edition):

Aridhi, S. (2013). Distributed frequent subgraph mining in the cloud : Fouille de sous-graphes fréquents dans les nuages. (Doctoral Dissertation). Université Blaise-Pascale, Clermont-Ferrand II. Retrieved from http://www.theses.fr/2013CLF22400

Chicago Manual of Style (16th Edition):

Aridhi, Sabeur. “Distributed frequent subgraph mining in the cloud : Fouille de sous-graphes fréquents dans les nuages.” 2013. Doctoral Dissertation, Université Blaise-Pascale, Clermont-Ferrand II. Accessed April 07, 2020. http://www.theses.fr/2013CLF22400.

MLA Handbook (7th Edition):

Aridhi, Sabeur. “Distributed frequent subgraph mining in the cloud : Fouille de sous-graphes fréquents dans les nuages.” 2013. Web. 07 Apr 2020.

Vancouver:

Aridhi S. Distributed frequent subgraph mining in the cloud : Fouille de sous-graphes fréquents dans les nuages. [Internet] [Doctoral dissertation]. Université Blaise-Pascale, Clermont-Ferrand II; 2013. [cited 2020 Apr 07]. Available from: http://www.theses.fr/2013CLF22400.

Council of Science Editors:

Aridhi S. Distributed frequent subgraph mining in the cloud : Fouille de sous-graphes fréquents dans les nuages. [Doctoral Dissertation]. Université Blaise-Pascale, Clermont-Ferrand II; 2013. Available from: http://www.theses.fr/2013CLF22400


Virginia Tech

12. Badr, Eman Mostafa. Identifying Splicing Regulatory Elements with de Bruijn Graphs.

Degree: PhD, Computer Science, 2015, Virginia Tech

 Splicing regulatory elements (SREs) are short, degenerate sequences on pre-mRNA molecules that enhance or inhibit the splicing process via the binding of splicing factors, proteins… (more)

Subjects/Keywords: Alternative splicing; de Bruijn graphs; algorithms; graph mining; splicing regulatory elements

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APA (6th Edition):

Badr, E. M. (2015). Identifying Splicing Regulatory Elements with de Bruijn Graphs. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73366

Chicago Manual of Style (16th Edition):

Badr, Eman Mostafa. “Identifying Splicing Regulatory Elements with de Bruijn Graphs.” 2015. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/73366.

MLA Handbook (7th Edition):

Badr, Eman Mostafa. “Identifying Splicing Regulatory Elements with de Bruijn Graphs.” 2015. Web. 07 Apr 2020.

Vancouver:

Badr EM. Identifying Splicing Regulatory Elements with de Bruijn Graphs. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/73366.

Council of Science Editors:

Badr EM. Identifying Splicing Regulatory Elements with de Bruijn Graphs. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/73366


Louisiana State University

13. Basuchowdhuri, Partha. Greedy methods for approximate graph matching with applications for social network analysis.

Degree: MSCS, Computer Sciences, 2009, Louisiana State University

 In this thesis, we study greedy algorithms for approximate sub-graph matching with attributed graphs. Such algorithms find one or multiple copies of a sub-graph pattern… (more)

Subjects/Keywords: Sub-Graph Mining; Seed; Social Network Analysis

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

APA (6th Edition):

Basuchowdhuri, P. (2009). Greedy methods for approximate graph matching with applications for social network analysis. (Masters Thesis). Louisiana State University. Retrieved from etd-04132009-134102 ; https://digitalcommons.lsu.edu/gradschool_theses/3105

Chicago Manual of Style (16th Edition):

Basuchowdhuri, Partha. “Greedy methods for approximate graph matching with applications for social network analysis.” 2009. Masters Thesis, Louisiana State University. Accessed April 07, 2020. etd-04132009-134102 ; https://digitalcommons.lsu.edu/gradschool_theses/3105.

MLA Handbook (7th Edition):

Basuchowdhuri, Partha. “Greedy methods for approximate graph matching with applications for social network analysis.” 2009. Web. 07 Apr 2020.

Vancouver:

Basuchowdhuri P. Greedy methods for approximate graph matching with applications for social network analysis. [Internet] [Masters thesis]. Louisiana State University; 2009. [cited 2020 Apr 07]. Available from: etd-04132009-134102 ; https://digitalcommons.lsu.edu/gradschool_theses/3105.

Council of Science Editors:

Basuchowdhuri P. Greedy methods for approximate graph matching with applications for social network analysis. [Masters Thesis]. Louisiana State University; 2009. Available from: etd-04132009-134102 ; https://digitalcommons.lsu.edu/gradschool_theses/3105

14. Bendimerad, Ahmed Anes. Mining useful patterns in attributed graphs : Exploration de modèles utiles dans les graphiques attribués.

Degree: Docteur es, Informatique, 2019, Lyon

Un graphe est une structure qui permet de modéliser efficacement une large variété de données. Par exemple, un réseau social peut être représenté avec un… (more)

Subjects/Keywords: Informatique; Fouille de données; Exploration de données; Motif; Graphes attribués; Modèle de données; Computer science; Data mining; Pattern mining; Attributed graphs; Graph; Data model; 006.310 72

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

APA (6th Edition):

Bendimerad, A. A. (2019). Mining useful patterns in attributed graphs : Exploration de modèles utiles dans les graphiques attribués. (Doctoral Dissertation). Lyon. Retrieved from http://www.theses.fr/2019LYSEI058

Chicago Manual of Style (16th Edition):

Bendimerad, Ahmed Anes. “Mining useful patterns in attributed graphs : Exploration de modèles utiles dans les graphiques attribués.” 2019. Doctoral Dissertation, Lyon. Accessed April 07, 2020. http://www.theses.fr/2019LYSEI058.

MLA Handbook (7th Edition):

Bendimerad, Ahmed Anes. “Mining useful patterns in attributed graphs : Exploration de modèles utiles dans les graphiques attribués.” 2019. Web. 07 Apr 2020.

Vancouver:

Bendimerad AA. Mining useful patterns in attributed graphs : Exploration de modèles utiles dans les graphiques attribués. [Internet] [Doctoral dissertation]. Lyon; 2019. [cited 2020 Apr 07]. Available from: http://www.theses.fr/2019LYSEI058.

Council of Science Editors:

Bendimerad AA. Mining useful patterns in attributed graphs : Exploration de modèles utiles dans les graphiques attribués. [Doctoral Dissertation]. Lyon; 2019. Available from: http://www.theses.fr/2019LYSEI058


New Jersey Institute of Technology

15. Bleik, Said. Concept graphs: Applications to biomedical text categorization and concept extraction.

Degree: PhD, Information Systems, 2013, New Jersey Institute of Technology

  As science advances, the underlying literature grows rapidly providing valuable knowledge mines for researchers and practitioners. The text content that makes up these knowledge… (more)

Subjects/Keywords: Text categorization; Concept extraction; Graph mining; Text mining; Graph representation; Concept graphs; Databases and Information Systems; Management Information Systems

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

APA (6th Edition):

Bleik, S. (2013). Concept graphs: Applications to biomedical text categorization and concept extraction. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/360

Chicago Manual of Style (16th Edition):

Bleik, Said. “Concept graphs: Applications to biomedical text categorization and concept extraction.” 2013. Doctoral Dissertation, New Jersey Institute of Technology. Accessed April 07, 2020. https://digitalcommons.njit.edu/dissertations/360.

MLA Handbook (7th Edition):

Bleik, Said. “Concept graphs: Applications to biomedical text categorization and concept extraction.” 2013. Web. 07 Apr 2020.

Vancouver:

Bleik S. Concept graphs: Applications to biomedical text categorization and concept extraction. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2013. [cited 2020 Apr 07]. Available from: https://digitalcommons.njit.edu/dissertations/360.

Council of Science Editors:

Bleik S. Concept graphs: Applications to biomedical text categorization and concept extraction. [Doctoral Dissertation]. New Jersey Institute of Technology; 2013. Available from: https://digitalcommons.njit.edu/dissertations/360

16. Bloemen, Vincent. Strong Connectivity and Shortest Paths for Checking Models.

Degree: 2019, NARCIS

 We study directed graphs and focus on algorithms for two classical graph problems; the decomposition of a graph into Strongly Connected Components (SCCs), and the… (more)

Subjects/Keywords: Algorithms; Model checking; Graph theory; Process mining; Automata

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APA (6th Edition):

Bloemen, V. (2019). Strong Connectivity and Shortest Paths for Checking Models. (Doctoral Dissertation). NARCIS. Retrieved from https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; ebdae062-2200-40de-ba24-a496f8bc1360 ; 10.3990/1.9789036547864 ; urn:isbn:978-90-365-4786-4 ; urn:isbn:978-90-365-4786-4 ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html

Chicago Manual of Style (16th Edition):

Bloemen, Vincent. “Strong Connectivity and Shortest Paths for Checking Models.” 2019. Doctoral Dissertation, NARCIS. Accessed April 07, 2020. https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; ebdae062-2200-40de-ba24-a496f8bc1360 ; 10.3990/1.9789036547864 ; urn:isbn:978-90-365-4786-4 ; urn:isbn:978-90-365-4786-4 ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html.

MLA Handbook (7th Edition):

Bloemen, Vincent. “Strong Connectivity and Shortest Paths for Checking Models.” 2019. Web. 07 Apr 2020.

Vancouver:

Bloemen V. Strong Connectivity and Shortest Paths for Checking Models. [Internet] [Doctoral dissertation]. NARCIS; 2019. [cited 2020 Apr 07]. Available from: https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; ebdae062-2200-40de-ba24-a496f8bc1360 ; 10.3990/1.9789036547864 ; urn:isbn:978-90-365-4786-4 ; urn:isbn:978-90-365-4786-4 ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html.

Council of Science Editors:

Bloemen V. Strong Connectivity and Shortest Paths for Checking Models. [Doctoral Dissertation]. NARCIS; 2019. Available from: https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; ebdae062-2200-40de-ba24-a496f8bc1360 ; 10.3990/1.9789036547864 ; urn:isbn:978-90-365-4786-4 ; urn:isbn:978-90-365-4786-4 ; urn:nbn:nl:ui:28-ebdae062-2200-40de-ba24-a496f8bc1360 ; https://research.utwente.nl/en/publications/strong-connectivity-and-shortest-paths-for-checking-models(ebdae062-2200-40de-ba24-a496f8bc1360).html

17. Boothe, Peter Mattison, 1978-. Measuring the Internet AS graph and its evolution.

Degree: 2009, University of Oregon

 As the Internet has evolved over time, the interconnection patterns of the members of this "network of networks" have changed. Can we characterize those changes?… (more)

Subjects/Keywords: Data mining; Graph theory; AS graph; Computer science

…all informed by ideas from networking, data mining, graph theory, and statistics. The… …including data mining, graph theory, algorithms, and networking. Along the way, we will use… …MEASURING THE INTERNET AS GRAPH AND ITS EVOLUTION by PETER MATTISON BOOTHE A… …Internet AS Graph and its Evolution" This dissertation has been accepted and approved in… …Title: MEASURING THE INTERNET AS GRAPH AND ITS EVOLUTION Approved: Dr. Andrzej Proskurowski… 

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

APA (6th Edition):

Boothe, Peter Mattison, 1. (2009). Measuring the Internet AS graph and its evolution. (Thesis). University of Oregon. Retrieved from http://hdl.handle.net/1794/10328

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):

Boothe, Peter Mattison, 1978-. “Measuring the Internet AS graph and its evolution.” 2009. Thesis, University of Oregon. Accessed April 07, 2020. http://hdl.handle.net/1794/10328.

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

MLA Handbook (7th Edition):

Boothe, Peter Mattison, 1978-. “Measuring the Internet AS graph and its evolution.” 2009. Web. 07 Apr 2020.

Vancouver:

Boothe, Peter Mattison 1. Measuring the Internet AS graph and its evolution. [Internet] [Thesis]. University of Oregon; 2009. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/1794/10328.

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

Council of Science Editors:

Boothe, Peter Mattison 1. Measuring the Internet AS graph and its evolution. [Thesis]. University of Oregon; 2009. Available from: http://hdl.handle.net/1794/10328

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

18. Bortner, Dustin P. Density-based clustering of information networks by substructure optimization.

Degree: MS, 0112, 2010, University of Illinois – Urbana-Champaign

 Information networks, such as biological or social networks, contain groups of related entities, which can be identified by clustering. Density-based clustering (DBC) differs from vertex-partitioning… (more)

Subjects/Keywords: density-based; clustering; networks; classification; graph mining; data mining

…is the upper-triangular adjacency matrix of the MST (a directed graph), and m is… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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

APA (6th Edition):

Bortner, D. P. (2010). Density-based clustering of information networks by substructure optimization. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/16220

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):

Bortner, Dustin P. “Density-based clustering of information networks by substructure optimization.” 2010. Thesis, University of Illinois – Urbana-Champaign. Accessed April 07, 2020. http://hdl.handle.net/2142/16220.

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

MLA Handbook (7th Edition):

Bortner, Dustin P. “Density-based clustering of information networks by substructure optimization.” 2010. Web. 07 Apr 2020.

Vancouver:

Bortner DP. Density-based clustering of information networks by substructure optimization. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2010. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/2142/16220.

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

Council of Science Editors:

Bortner DP. Density-based clustering of information networks by substructure optimization. [Thesis]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/16220

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


Université de Lorraine

19. Bresso, Emmanuel. Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs : Organization and exploitation of biological molecular networks for studying the etiology of genetic diseases and for characterizing drug side effects.

Degree: Docteur es, Sciences de la vie et de la santé, 2013, Université de Lorraine

La compréhension des pathologies humaines et du mode d'action des médicaments passe par la prise en compte des réseaux d'interactions entre biomolécules. Les recherches récentes… (more)

Subjects/Keywords: Réseaux d'interactions; Intégration de données; Visualisation de graphes; Fouille de données relationnelle; Compréhension des effets secondaires; Relations génotype-phénotype; Interaction networks; Data integration; Graph visualization; Relational data mining; Understanding of drug side-effects; Genotype-phenotype relationships; 572.8

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APA (6th Edition):

Bresso, E. (2013). Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs : Organization and exploitation of biological molecular networks for studying the etiology of genetic diseases and for characterizing drug side effects. (Doctoral Dissertation). Université de Lorraine. Retrieved from http://www.theses.fr/2013LORR0122

Chicago Manual of Style (16th Edition):

Bresso, Emmanuel. “Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs : Organization and exploitation of biological molecular networks for studying the etiology of genetic diseases and for characterizing drug side effects.” 2013. Doctoral Dissertation, Université de Lorraine. Accessed April 07, 2020. http://www.theses.fr/2013LORR0122.

MLA Handbook (7th Edition):

Bresso, Emmanuel. “Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs : Organization and exploitation of biological molecular networks for studying the etiology of genetic diseases and for characterizing drug side effects.” 2013. Web. 07 Apr 2020.

Vancouver:

Bresso E. Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs : Organization and exploitation of biological molecular networks for studying the etiology of genetic diseases and for characterizing drug side effects. [Internet] [Doctoral dissertation]. Université de Lorraine; 2013. [cited 2020 Apr 07]. Available from: http://www.theses.fr/2013LORR0122.

Council of Science Editors:

Bresso E. Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs : Organization and exploitation of biological molecular networks for studying the etiology of genetic diseases and for characterizing drug side effects. [Doctoral Dissertation]. Université de Lorraine; 2013. Available from: http://www.theses.fr/2013LORR0122


Brno University of Technology

20. Bruckner, Tomáš. Rekonstrukce zachycené komunikace a dolování dat na sociální síti Facebook .

Degree: 2015, Brno University of Technology

 Tato práce se zabývá sociální síti Facebook z pohledu počítačové forenzní vědy se zaměřením na získávání citlivých a potenciálně užitečných informací o sledovaných uživatelích. Cílem… (more)

Subjects/Keywords: Facebook; Man-in-the-Middle; rekonstrukce dat; dolování dat; NetFox; SSL; HTTPS; Graph API; Selenium;  Diffie-Hellman; RSA; Facebook; Man-in-the-Middle; data reconstruction; data mining; NetFox; SSL; HTTPS; Graph API; Selenium; Diffie-Hellman; RSA

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APA (6th Edition):

Bruckner, T. (2015). Rekonstrukce zachycené komunikace a dolování dat na sociální síti Facebook . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/52425

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):

Bruckner, Tomáš. “Rekonstrukce zachycené komunikace a dolování dat na sociální síti Facebook .” 2015. Thesis, Brno University of Technology. Accessed April 07, 2020. http://hdl.handle.net/11012/52425.

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

MLA Handbook (7th Edition):

Bruckner, Tomáš. “Rekonstrukce zachycené komunikace a dolování dat na sociální síti Facebook .” 2015. Web. 07 Apr 2020.

Vancouver:

Bruckner T. Rekonstrukce zachycené komunikace a dolování dat na sociální síti Facebook . [Internet] [Thesis]. Brno University of Technology; 2015. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/11012/52425.

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

Council of Science Editors:

Bruckner T. Rekonstrukce zachycené komunikace a dolování dat na sociální síti Facebook . [Thesis]. Brno University of Technology; 2015. Available from: http://hdl.handle.net/11012/52425

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


East Carolina University

21. Budhathoki, Dev. Knowledge Discovery for Clinical Decision Support System in Patient Records.

Degree: 2018, East Carolina University

 Knowledge discovery from the patient's health records is a challenging task for the medical specialists. The knowledge generated from the patient's records can assist specialists… (more)

Subjects/Keywords: Neo4j Graph Database; Knowledge Extraction; Clinical Decision Support System; Cypher Query Language; Medical records – Data processing; Association rule mining

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APA (6th Edition):

Budhathoki, D. (2018). Knowledge Discovery for Clinical Decision Support System in Patient Records. (Thesis). East Carolina University. Retrieved from http://hdl.handle.net/10342/6965

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):

Budhathoki, Dev. “Knowledge Discovery for Clinical Decision Support System in Patient Records.” 2018. Thesis, East Carolina University. Accessed April 07, 2020. http://hdl.handle.net/10342/6965.

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

MLA Handbook (7th Edition):

Budhathoki, Dev. “Knowledge Discovery for Clinical Decision Support System in Patient Records.” 2018. Web. 07 Apr 2020.

Vancouver:

Budhathoki D. Knowledge Discovery for Clinical Decision Support System in Patient Records. [Internet] [Thesis]. East Carolina University; 2018. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10342/6965.

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

Council of Science Editors:

Budhathoki D. Knowledge Discovery for Clinical Decision Support System in Patient Records. [Thesis]. East Carolina University; 2018. Available from: http://hdl.handle.net/10342/6965

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


University of Florida

22. Busygin, Stanislav. Combinatorial Optimization Techniques in Data Mining.

Degree: PhD, Industrial and Systems Engineering, 2007, University of Florida

 My research analyzes the role of combinatorial optimization in data mining research and proposes a collection of new practically efficient data mining techniques based on… (more)

Subjects/Keywords: Algorithms; Carts; Data analysis; Datasets; Heuristics; Information classification; Linear programming; Matrices; Mining; Vertices; algorithm, analysis, biclustering, classification, clique, clustering, data, graph, optimization

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

APA (6th Edition):

Busygin, S. (2007). Combinatorial Optimization Techniques in Data Mining. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0021157

Chicago Manual of Style (16th Edition):

Busygin, Stanislav. “Combinatorial Optimization Techniques in Data Mining.” 2007. Doctoral Dissertation, University of Florida. Accessed April 07, 2020. http://ufdc.ufl.edu/UFE0021157.

MLA Handbook (7th Edition):

Busygin, Stanislav. “Combinatorial Optimization Techniques in Data Mining.” 2007. Web. 07 Apr 2020.

Vancouver:

Busygin S. Combinatorial Optimization Techniques in Data Mining. [Internet] [Doctoral dissertation]. University of Florida; 2007. [cited 2020 Apr 07]. Available from: http://ufdc.ufl.edu/UFE0021157.

Council of Science Editors:

Busygin S. Combinatorial Optimization Techniques in Data Mining. [Doctoral Dissertation]. University of Florida; 2007. Available from: http://ufdc.ufl.edu/UFE0021157


Virginia Tech

23. Cadena, Jose Eduardo. Finding Interesting Subgraphs with Guarantees.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Networks are a mathematical abstraction of the interactions between a set of entities, with extensive applications in social science, epidemiology, bioinformatics, and cybersecurity, among others.… (more)

Subjects/Keywords: Graph Mining; Data Mining; Graph Algorithms; Anomaly Detection; Finding Subgraphs; Parameterized Complexity; Distributed Algorithms

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

APA (6th Edition):

Cadena, J. E. (2018). Finding Interesting Subgraphs with Guarantees. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81960

Chicago Manual of Style (16th Edition):

Cadena, Jose Eduardo. “Finding Interesting Subgraphs with Guarantees.” 2018. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/81960.

MLA Handbook (7th Edition):

Cadena, Jose Eduardo. “Finding Interesting Subgraphs with Guarantees.” 2018. Web. 07 Apr 2020.

Vancouver:

Cadena JE. Finding Interesting Subgraphs with Guarantees. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/81960.

Council of Science Editors:

Cadena JE. Finding Interesting Subgraphs with Guarantees. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/81960

24. Cakmak, Ali. Mining Metabolic Networks and Biomedical Literature.

Degree: PhD, EECS - Computer and Information Sciences, 2009, Case Western Reserve University

  With the advent of high-throughput experimental and genome sequencing technologies, the amounts of produced biological data and the related literature have increased dramatically. A… (more)

Subjects/Keywords: Bioinformatics; Computer Science; pathway inference; text mining; gene ontology; metabolic networks; metabolomics; graph mining; taxonomy-superimposed graph mining; data mining; pathway functionality template

…23 1.2 Taxonomy-Superimposed Graph Mining… …133 Taxonomy-Superimposed Graph Mining… …141 6.3 Properties of Taxonomy-Superimposed Graph Mining… …291 12.2 Taxonomy-Superimposed Graph Mining… …into a purely computer science problem, namely, that of mining taxonomy-superimposed graph… 

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

APA (6th Edition):

Cakmak, A. (2009). Mining Metabolic Networks and Biomedical Literature. (Doctoral Dissertation). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1223490345

Chicago Manual of Style (16th Edition):

Cakmak, Ali. “Mining Metabolic Networks and Biomedical Literature.” 2009. Doctoral Dissertation, Case Western Reserve University. Accessed April 07, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1223490345.

MLA Handbook (7th Edition):

Cakmak, Ali. “Mining Metabolic Networks and Biomedical Literature.” 2009. Web. 07 Apr 2020.

Vancouver:

Cakmak A. Mining Metabolic Networks and Biomedical Literature. [Internet] [Doctoral dissertation]. Case Western Reserve University; 2009. [cited 2020 Apr 07]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1223490345.

Council of Science Editors:

Cakmak A. Mining Metabolic Networks and Biomedical Literature. [Doctoral Dissertation]. Case Western Reserve University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1223490345

25. Cameron, Delroy Huborn. A Context-Driven Subgraph Model for Literature-Based Discovery.

Degree: PhD, Computer Science and Engineering PhD, 2014, Wright State University

 Literature-Based Discovery (LBD) refers to the process of uncovering hidden connections that are implicit in scientific literature. Numerous hypotheses have been generated from scientific literature… (more)

Subjects/Keywords: Computer Science; Biomedical Research; Information Systems; Semantic Predications; Graph mining; Path clustering; Semantic relatedness; Literature-based discovery

…biomedical text mining in Section 2.1, which includes Information Retrieval (IR)… …Text Mining Harnessing information from biomedical texts for knowledge discovery is generally… …considered a subtask of Biomedical Text Mining. In Computer Science, Text Mining “refers to the… …process of deriving high quality information from text” [26]. Biomedical Text Mining… …biomedical texts. Generally, biomedical text mining [76] can be perceived as being… 

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

APA (6th Edition):

Cameron, D. H. (2014). A Context-Driven Subgraph Model for Literature-Based Discovery. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001

Chicago Manual of Style (16th Edition):

Cameron, Delroy Huborn. “A Context-Driven Subgraph Model for Literature-Based Discovery.” 2014. Doctoral Dissertation, Wright State University. Accessed April 07, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001.

MLA Handbook (7th Edition):

Cameron, Delroy Huborn. “A Context-Driven Subgraph Model for Literature-Based Discovery.” 2014. Web. 07 Apr 2020.

Vancouver:

Cameron DH. A Context-Driven Subgraph Model for Literature-Based Discovery. [Internet] [Doctoral dissertation]. Wright State University; 2014. [cited 2020 Apr 07]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001.

Council of Science Editors:

Cameron DH. A Context-Driven Subgraph Model for Literature-Based Discovery. [Doctoral Dissertation]. Wright State University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001

26. Canu, Maël. Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux : Vertex centred community detection for opportunistic mobile social networks.

Degree: Docteur es, Informatique, 2017, Université Pierre et Marie Curie – Paris VI

Les travaux présentés dans la thèse s'inscrivent dans le cadre de l'analyse des graphes de terrain (complex networks) et plus précisément de la tâche de… (more)

Subjects/Keywords: Data mining; Fouille de graphes; Détection de communautés; Graphe dynamique; Méthode décentralisée; Méthode orientée sommet; Communautés recouvrantes; Vertex centred community detection; Dynamic graph; Network analysis; 004

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APA (6th Edition):

Canu, M. (2017). Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux : Vertex centred community detection for opportunistic mobile social networks. (Doctoral Dissertation). Université Pierre et Marie Curie – Paris VI. Retrieved from http://www.theses.fr/2017PA066378

Chicago Manual of Style (16th Edition):

Canu, Maël. “Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux : Vertex centred community detection for opportunistic mobile social networks.” 2017. Doctoral Dissertation, Université Pierre et Marie Curie – Paris VI. Accessed April 07, 2020. http://www.theses.fr/2017PA066378.

MLA Handbook (7th Edition):

Canu, Maël. “Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux : Vertex centred community detection for opportunistic mobile social networks.” 2017. Web. 07 Apr 2020.

Vancouver:

Canu M. Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux : Vertex centred community detection for opportunistic mobile social networks. [Internet] [Doctoral dissertation]. Université Pierre et Marie Curie – Paris VI; 2017. [cited 2020 Apr 07]. Available from: http://www.theses.fr/2017PA066378.

Council of Science Editors:

Canu M. Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux : Vertex centred community detection for opportunistic mobile social networks. [Doctoral Dissertation]. Université Pierre et Marie Curie – Paris VI; 2017. Available from: http://www.theses.fr/2017PA066378

27. C.C. Monti. MODELING AND MINING COMPLEX NETWORKS WITH FEATURE-RICH NODES.

Degree: 2017, Università degli Studi di Milano

 Real-world complex networks describe connections between objects; in reality, those objects are typically endowed with features. How does the presence or absence of such features… (more)

Subjects/Keywords: complex networks; machine learning; social networks; graphs; data mining; graph mining; label prediction; link prediction; Settore INF/01 - Informatica; Settore MAT/06 - Probabilita' e Statistica Matematica

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

APA (6th Edition):

Monti, C. (2017). MODELING AND MINING COMPLEX NETWORKS WITH FEATURE-RICH NODES. (Thesis). Università degli Studi di Milano. Retrieved from http://hdl.handle.net/2434/485805

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):

Monti, C.C.. “MODELING AND MINING COMPLEX NETWORKS WITH FEATURE-RICH NODES.” 2017. Thesis, Università degli Studi di Milano. Accessed April 07, 2020. http://hdl.handle.net/2434/485805.

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

MLA Handbook (7th Edition):

Monti, C.C.. “MODELING AND MINING COMPLEX NETWORKS WITH FEATURE-RICH NODES.” 2017. Web. 07 Apr 2020.

Vancouver:

Monti C. MODELING AND MINING COMPLEX NETWORKS WITH FEATURE-RICH NODES. [Internet] [Thesis]. Università degli Studi di Milano; 2017. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/2434/485805.

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

Council of Science Editors:

Monti C. MODELING AND MINING COMPLEX NETWORKS WITH FEATURE-RICH NODES. [Thesis]. Università degli Studi di Milano; 2017. Available from: http://hdl.handle.net/2434/485805

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


Case Western Reserve University

28. Cederquist, Aaron. Frequent Pattern Mining among Weighted and Directed Graphs.

Degree: MSs, EECS - Computer and Information Sciences, 2009, Case Western Reserve University

Mining frequent graph patterns has great practical implications, since data in numerous application domains such as biology, sociology, and finance, can be represented as graphs.… (more)

Subjects/Keywords: Computer Science; data mining; graph; canonical form; frequent pattern mining

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

APA (6th Edition):

Cederquist, A. (2009). Frequent Pattern Mining among Weighted and Directed Graphs. (Masters Thesis). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1228328123

Chicago Manual of Style (16th Edition):

Cederquist, Aaron. “Frequent Pattern Mining among Weighted and Directed Graphs.” 2009. Masters Thesis, Case Western Reserve University. Accessed April 07, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1228328123.

MLA Handbook (7th Edition):

Cederquist, Aaron. “Frequent Pattern Mining among Weighted and Directed Graphs.” 2009. Web. 07 Apr 2020.

Vancouver:

Cederquist A. Frequent Pattern Mining among Weighted and Directed Graphs. [Internet] [Masters thesis]. Case Western Reserve University; 2009. [cited 2020 Apr 07]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1228328123.

Council of Science Editors:

Cederquist A. Frequent Pattern Mining among Weighted and Directed Graphs. [Masters Thesis]. Case Western Reserve University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1228328123


NSYSU

29. Chang, Shih-Ta. MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET.

Degree: Master, Information Management, 2000, NSYSU

 This thesis focuses on mining user access patterns from netflow database collected from the core router of a regional network center. We use the attributed… (more)

Subjects/Keywords: generalization; access patterns; large graph; graph similarity and distance; error-correcting graph matching; deviation detection; data mining; attributed releated graph

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

APA (6th Edition):

Chang, S. (2000). MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0718100-133038

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):

Chang, Shih-Ta. “MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET.” 2000. Thesis, NSYSU. Accessed April 07, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0718100-133038.

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

MLA Handbook (7th Edition):

Chang, Shih-Ta. “MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET.” 2000. Web. 07 Apr 2020.

Vancouver:

Chang S. MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET. [Internet] [Thesis]. NSYSU; 2000. [cited 2020 Apr 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0718100-133038.

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

Council of Science Editors:

Chang S. MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET. [Thesis]. NSYSU; 2000. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0718100-133038

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


Penn State University

30. Chatterjee, Anirban. Exploiting Sparsity, Structure, and Geometry for Knowledge Discovery.

Degree: PhD, Computer Science and Engineering, 2011, Penn State University

 Data-driven discovery seeks to obtain a computational model of the underlying process using observed data on a large number of variables. Observations can be viewed… (more)

Subjects/Keywords: sparse graph embedding; sparse graph partitioning; data mining; sparse linear solvers

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

APA (6th Edition):

Chatterjee, A. (2011). Exploiting Sparsity, Structure, and Geometry for Knowledge Discovery. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/12026

Chicago Manual of Style (16th Edition):

Chatterjee, Anirban. “Exploiting Sparsity, Structure, and Geometry for Knowledge Discovery.” 2011. Doctoral Dissertation, Penn State University. Accessed April 07, 2020. https://etda.libraries.psu.edu/catalog/12026.

MLA Handbook (7th Edition):

Chatterjee, Anirban. “Exploiting Sparsity, Structure, and Geometry for Knowledge Discovery.” 2011. Web. 07 Apr 2020.

Vancouver:

Chatterjee A. Exploiting Sparsity, Structure, and Geometry for Knowledge Discovery. [Internet] [Doctoral dissertation]. Penn State University; 2011. [cited 2020 Apr 07]. Available from: https://etda.libraries.psu.edu/catalog/12026.

Council of Science Editors:

Chatterjee A. Exploiting Sparsity, Structure, and Geometry for Knowledge Discovery. [Doctoral Dissertation]. Penn State University; 2011. Available from: https://etda.libraries.psu.edu/catalog/12026

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