<div> <div> <div> <p>The use of graph-structured data in applications is increasing day by day. In order to infer useful information from such data, fast analytics and software tools are required. One of the graph analytics techniques used is community detection. Community detection is the technique of finding structural communities within a graph. Such communities are defined as groups which have highly connected nodes and have similarities with each other. </p> <p>This research proposes a parallel heuristic for faster community detection using the parallel version of the Louvain algorithm: Grappolo. The Louvain algorithm is a hierarchical algorithm that focuses on modularity optimization. It gained popularity because of its ability to detect high-quality communities faster than the other existing community detection algorithms. However, the Louvain algorithm is a sequential algorithm. To reduce the execution time of the Louvain algorithm, a parallel version named Grappolo exists in the literature. This algorithm proposes parallel heuristics that address the challenges that occur due to parallelizing the sequential Louvain algorithm. </p> <p>In this study, the researcher is investigating if Grappolo can be further parallelized to further reduce the execution time maintaining the quality of communities detected. To evaluate the proposed heuristic, it was tested on an OpenMP multithreaded environment. It was implemented on source codes of Android malware applications. However, as compared to Grapplolo, the proposed modified version resulted in higher execution times for the inputs tested. The modularity of the communities detected was similar to the Grappolo implementation. </p> </div> </div> </div>

During this "white collar recession,'' there is a flooded labor market of workers. For employers seeking to hire, there is a need to identify potential qualified candidates for each job. The current state of the art is LinkedIn Recruiting or elastic search on Resumes. The current state of the art lacks efficiency and scalability along with an intuitive ranking of candidates. We believe this can be fixed with multi-layer categorical clustering via modularity maximization. To test this, we gathered a dataset that is extensive and representative of the job market. Our data comes from PeopleDataLabs and LinkedIn and is sampled from 153 million individuals. As such, this data represents one of the most informative datasets for the task of ranking and clustering job titles and skills. Properly grouping individuals will help identify more candidates to fulfill the multitude of vacant positions. We implement a novel framework for categorical clustering, involving these attributes to deliver a reliable pool of candidates. We develop a metric for clustering based on commonality to rank clustering algorithms. The metric prefers modularity-based clustering algorithms like the Louvain algorithm. This allows us to use such algorithms to outperform other unsupervised methods for categorical clustering. Our implementation accurately clusters emergency services, health-care and other fields while managerial positions are interestingly swamped by soft or uninformative features thereby resulting in dominant ambiguous clusters.

The personalization of online advertising has now become a necessity for marketing agencies. The tracking technologies such as third-party cookies gives advertisers the ability to recognize internet users across different websites, to understand their behavior and to assess their needs and their tastes. The amount of created data and interactions leads to the creation of a large cross-device identity graph that links different identifiers such as emails to different devices used on different networks. Over time, strongly connected components appear in this graph, too large to represent only the identifiers or devices of only one person or household. The aims of this project is to partition these components according to the structure of the graph and the features associated to the edges without separating identifiers used by a same person. Subsequent to this, the size reduction of these components leads to the isolation of individuals and the identifiers associated to them. This thesis presents the design of a bipartite graph from the available data, the implementation of different community detection graphs adapted to this specific case and different validation methods designed to assess the quality of our partition. Different graph metrics are then used to compare the outputs of the algorithms and we will observe how the adaptation of the algorithm to the bipartite case can lead to better results. / Anpassningen av onlineannonsering har nu blivit en nödvändighet för marknadsföringsbyråer. Spårningstekniken som cookies från tredje part ger annonsörer möjlighet att känna igen internetanvändare på olika webbplatser, för att förstå deras beteende och för att bedöma deras behov och deras smak. Mängden skapade data och interaktioner leder till skapandet av en stor identitetsgrafik för flera enheter som länkar olika identifierare, t.ex. e-postmeddelanden till olika enheter som används i olika nätverk. Över tiden visas starkt anslutna komponenter i det här diagrammet, för stora för att endast representera identifierare eller enheter av endast en person eller hushåll. Syftet med detta projekt är att partitionera dessa komponenter enligt grafens struktur och de egenskaper som är knutna till kanterna utan att separera identifierare som används av samma person. Efter detta leder storleksreduktionen av dessa komponenter till isoleringen av individer och de identifierare som är associerade med dem. Denna avhandling presenterar utformningen av en bifogad graf från tillgängliga data, genomförandet av olika samhällsdetekteringskurvor anpassade till detta specifika fall och olika valideringsmetoder som är utformade för att bedöma kvaliteten på vår partition. Olika grafvärden används då för att jämföra algoritmens utgångar och vi kommer att observera hur anpassningen av algoritmen till tvåpartsfallet kan leda till bättre resultat.

Community detection (or clustering) in large-scale graph is an important problem in graph mining. Communities reveal interesting characteristics of a network. Louvain is an efficient sequential algorithm but fails to scale emerging large-scale data. Developing distributed-memory parallel algorithms is challenging because of inter-process communication and load-balancing issues. In this work, we design a shared memory-based algorithm using OpenMP, which shows a 4-fold speedup but is limited to available physical cores. Our second algorithm is an MPI-based parallel algorithm that scales to a moderate number of processors. We also implement a hybrid algorithm combining both. Finally, we incorporate dynamic load-balancing in our final algorithm DPLAL (Distributed Parallel Louvain Algorithm with Load-balancing). DPLAL overcomes the performance bottleneck of the previous algorithms, shows around 12-fold speedup scaling to a larger number of processors. Overall, we present the challenges, our solutions, and the empirical performance of our algorithms for several large real-world networks.

Cette thèse a pour objet l’étude des hôpitaux dans les villes du duché de Brabant, depuis leur apparition, à l’aube du XIIe siècle, jusqu’au XVe siècle, époque de transition dans l’organisation de la bienfaisance urbaine. L’accent est mis particulièrement sur l’analyse de l’environnement social, économique et politique qui encourage la fondation de ces établissements et en accompagne le développement.Une première partie envisage les fondations de manière chronologique, distinguant plusieurs périodes de croissance, entrecoupées de longues pauses. Chaque période voit l’intervention d’acteurs particuliers qui prennent en main fondation, dotation et gestion de ces établissements. La seconde partie étudie de manière plus transversale la fondation, la gestion et l’utilisation d’une série d’établissements du XIVe siècle destinés à l’accueil de courte durée, qualifiés ici de gasthuizen. Les acteurs de leur existence sont répartis en trois segments :le groupe fondateur, les administrateurs et la communauté, au sens large, de l’hôpital.Tout au long de la thèse, une place centrale est donnée à la question de l’usage de l’hôpital. Depuis sa fondation ou son administration, jusqu’à l’emploi de son patrimoine ou la mobilisation de sa confrérie, l’hôpital peut en effet servir des objectifs très divers qu’ils soient religieux, politiques, économiques ou d’ascension sociale. Il apparait que, pour qui sait s’en servir, l’hôpital est un outil à multiples facettes. / This PhD thesis studies the hospitals in the cities of the Duchy of Brabant, from their emergence in the early 12th century until the 15th century. The emphasis lies mostly on the analysis of the economic, political and social context from which they rise and where they thrive. Through the thesis, the main actors of the hospital's life are identified and their motives scrutinised. The hospital appears to be indeed a very convenient tool, to use according various economic, political or social purposes. / Doctorat en Histoire, histoire de l'art et archéologie / info:eu-repo/semantics/nonPublished

Botnets are a global problem, and effective botnet detection requires cooperation of large Internet Service Providers, allowing near global visibility of traffic that can be exploited to detect them. The global visibility comes with huge challenges, especially in the amount of data that has to be analysed. To handle such large volumes of data, a robust and effective detection method is the need of the hour and it must rely primarily on a reduced or abstracted form of data such as a graph of hosts, with the presence of an edge between two hosts if there is any data communication between them. Such an abstraction would be easy to construct and store, as very little of the packet needs to be looked at. Structured P2P command and control have been shown to be robust against targeted and random node failures, thus are ideal mechanisms for botmasters to organize and command their botnets effectively. Thus this thesis develops a scalable, efficient and robust algorithm for the detection of structured P2P botnets in large traffic graphs. It draws from the advances in the state of the art in Community Detection, which aim to partition a graph into dense communities. Popular Community Detection Algorithms with low theoretical time complexities such as Label Propagation, Infomap and Louvain Method have been implemented and compared on large LFR benchmark graphs to study their efficiency. Louvain method is found to be capable of handling graphs of millions of vertices and billions of edges. This thesis analyses the performance of this method with two objective functions, Modularity and Stability and found that neither of them are robust and general. In order to overcome the limitations of these objective functions, a third objective function proposed in the literature is considered. This objective function has previously been used in the case of Protein Interaction Networks successfully, and used in this thesis to detect structured P2P botnets for the first time. Further, the differences in the topological properties - assortativity and density, of structured P2P botnet communities and benign communities are discussed. In order to exploit these differences, a novel measure based on mean regular degree is proposed, which captures both the assortativity and the density of a graph and its properties are studied. This thesis proposes a robust and efficient algorithm that combines the use of greedy community detection and community filtering using the proposed measure mean regular degree. The proposed algorithm is tested extensively on a large number of datasets and found to be comparable in performance in most cases to an existing botnet detection algorithm called BotGrep and found to be significantly faster.

Prima parte: L'analisi del rapporto tra spiritualità certosina e devotio moderna consente di individuare il contesto in cui maturò ed ebbe fortuna il De tralatione Bibliae di Petrus Sutor, monaco certosino. La spiritualità certosina ebbe forte influsso sulla Congregazione di Montaigu, espressione estrema della devotio moderna, nella quale lo stesso Sutor fu massima autorità spirituale in qualità di priore della Certosa di Parigi. Alla Congregazione di Montaigu appartennero i principali oppositori di Erasmo nel campo della filologia biblica nell'area di Parigi e Lovanio. In essa ebbe fortuna l'opera di Sutor, anche se il mondo di Montaigu mostra due facce. Il mondo parigino di Montaigu risulta infatti più conservatore di quello lovaniense, che nelle figure di Iacobus Latomus e Frans Titelmans mostra una certa apertura all'umanesimo. Seconda parte e appendice: i contenuti del De tralatione Bibliae mostrano i rapporti di Sutor con altri oppositori erasmiani, Stunica in particolare. Emergono le fonti che stanno alla base delle informazioni storiche fornite da Sutor, tra cui emerge Petrus Comestor, e la risonanza del De tralatione Bibliae negli ambienti culturali inglesi, in particolare in John Fisher. / First Part: In order to supply with due context Sutor's De tralatione Bibliae, it is necessary to rediscover the interplay between Carthusian spirituality and devotio moderna. The carthusian influence was particulary strong in the Congregation of Montaigu, which formed an extreme wing of devotio moderna. Sutor himself played a very important role in the Congregation of Montaigu having been his major authority for three years as Prior of the Parisian Charterhouse. The main critics of Erasmus in the field of biblical philology, who were active in Paris and Louvain theological units belonged to the Montaigu Congregation. There were differences between the Paris and Louvain Montaigu cultural and spiritual habits. Louvain shows a particular trend to moderation and acceptance of some fundamental humanistic issues, that we can trace in Iacobus Latomus and Francis Titelmans. Second Part and Appendix: The contents of Sutor's De tralatione Bibliae display the relationship between Sutor and other critics of Erasmus, in particular Stunica. Through the text we rediscover the different sources Sutor uses in order to supply the reader with historical information, especially Petrus Comestor, and we can identify some echoes of Sutor's works in John Fisher and the English cultural circles.