Relevant bibliographies by topics / Document network

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Document network'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Document network"

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Zhang, Ce, and Hady W. Lauw. "Topic Modeling on Document Networks with Adjacent-Encoder." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6737–45. http://dx.doi.org/10.1609/aaai.v34i04.6152.

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Oftentimes documents are linked to one another in a network structure,e.g., academic papers cite other papers, Web pages link to other pages. In this paper we propose a holistic topic model to learn meaningful and unified low-dimensional representations for networked documents that seek to preserve both textual content and network structure. On the basis of reconstructing not only the input document but also its adjacent neighbors, we develop two neural encoder architectures. Adjacent-Encoder, or AdjEnc, induces competition among documents for topic propagation, and reconstruction among neighbors for semantic capture. Adjacent-Encoder-X, or AdjEnc-X, extends this to also encode the network structure in addition to document content. We evaluate our models on real-world document networks quantitatively and qualitatively, outperforming comparable baselines comprehensively.
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Noel, Steven, Chee-Hung Henry Chu, and Vijay Raghavan. "Co-Citation Count vs Correlation for Influence Network Visualization." Information Visualization 2, no. 3 (September 2003): 160–70. http://dx.doi.org/10.1057/palgrave.ivs.9500049.

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Visualization of author or document influence networks as a two-dimensional image can provide key insights into the direct influence of authors or documents on each other in a document collection. The influence network is constructed based on the minimum spanning tree, in which the nodes are documents and an edge is the most direct influence between two documents. Influence network visualizations have typically relied on co-citation correlation as a measure of document similarity. That is, the similarity between two documents is computed by correlating the sets of citations to each of the two documents. In a different line of research, co-citation count (the number of times two documents are jointly cited) has been applied as a document similarity measure. In this work, we demonstrate the impact of each of these similarity measures on the document influence network. We provide examples, and analyze the significance of the choice of similarity measure. We show that correlation-based visualizations exhibit chaining effects (low average vertex degree), a manifestation of multiple minor variations in document similarities. These minor similarity variations are absent in count-based visualizations. The result is that count-based influence network visualizations are more consistent with the intuitive expectation of authoritative documents being hubs that directly influence large numbers of documents.
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Yerokhin, A. L., and O. V. Zolotukhin. "Fuzzy probabilistic neural network in document classification tasks." Information extraction and processing 2018, no. 46 (December 27, 2018): 68–71. http://dx.doi.org/10.15407/vidbir2018.46.068.

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Bai, Juho, Inwook Shim, and Seog Park. "MEXN: Multi-Stage Extraction Network for Patent Document Classification." Applied Sciences 10, no. 18 (September 8, 2020): 6229. http://dx.doi.org/10.3390/app10186229.

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The patent document has different content for each paragraph, and the length of the document is also very long. Moreover, patent documents are classified hierarchically as multi-labels. Many works have employed deep neural architectures to classify the patent documents. Traditional document classification methods have not well represented the characteristics of entire patent document contents because they usually require a fixed input length. To address this issue, we propose a neural network-based document classification for patent documents by designing a novel multi-stage feature extraction network (MEXN), which comprise of paragraphs encoder and summarizer for all paragraphs. MEXN features analysis of the whole documents hierarchically and providing multi-labels outputs. Furthermore, MEXN preserves computing performance marginally increase. We demonstrate that the proposed method outperforms current state-of-the-art models in patent document classification tasks with multi-label classification experiments for USPD datasets.
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Zheng, Jianming, Yupu Guo, Chong Feng, and Honghui Chen. "A Hierarchical Neural-Network-Based Document Representation Approach for Text Classification." Mathematical Problems in Engineering 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/7987691.

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Document representation is widely used in practical application, for example, sentiment classification, text retrieval, and text classification. Previous work is mainly based on the statistics and the neural networks, which suffer from data sparsity and model interpretability, respectively. In this paper, we propose a general framework for document representation with a hierarchical architecture. In particular, we incorporate the hierarchical architecture into three traditional neural-network models for document representation, resulting in three hierarchical neural representation models for document classification, that is, TextHFT, TextHRNN, and TextHCNN. Our comprehensive experimental results on two public datasets, that is, Yelp 2016 and Amazon Reviews (Electronics), show that our proposals with hierarchical architecture outperform the corresponding neural-network models for document classification, resulting in a significant improvement ranging from 4.65% to 35.08% in terms of accuracy with a comparable (or substantially less) expense of time consumption. In addition, we find that the long documents benefit more from the hierarchical architecture than the short ones as the improvement in terms of accuracy on long documents is greater than that on short documents.
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CHEN, YANPING, QINGHUA ZHENG, FENG TIAN, HUAN LIU, YAZHOU HAO, and NAZARAF SHAH. "Exploring open information via event network." Natural Language Engineering 24, no. 2 (October 26, 2017): 199–220. http://dx.doi.org/10.1017/s1351324917000390.

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AbstractIt is a challenging task to discover information from a large amount of data in an open domain.1 In this paper, an event network framework is proposed to address this challenge. It is in fact an empirical construct for exploring open information, composed of three steps: document event detection, event network construction and event network analysis. First, documents are clustered into document events for reducing the impact of noisy and heterogeneous resources. Secondly, linguistic units (e.g., named entities or entity relations) are extracted from each document event and combined into an event network, which enables content-oriented retrieval. Then, in the final step, techniques such as social network or complex network can be applied to analyze the event network for exploring open information. In the implementation section, we provide examples of exploring open information via event network.
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Gupta, Akanksha, Ravindra Pratap Narwaria, and Madhav Singh. "Review on Deep Learning Handwritten Digit Recognition using Convolutional Neural Network." International Journal of Recent Technology and Engineering 9, no. 5 (January 30, 2021): 245–47. http://dx.doi.org/10.35940/ijrte.e5287.019521.

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In this digital world, everything including documents, notes is kept in digital form. The requirement of converting these digital documents into processed information is in demand. This process is called as Handwritten digit recognition (HDR). The digital scan document is processed and classified to identify the hand written words into digital text so that it can be used to keep it in the documents format means in computerized font so that everybody can read it properly. In this paper, it is discussed that classifiers like KNN, SVM, CNN are used for HDR. These classifiers are trained with some predefined dataset and then used to process any digital scan document into computer document format. The scanned document is passed through four different stages for recognition where image is preprocessed, segmented and then recognized by classifier. MNIST dataset is used for training purpose. Complete CNN classifier is discussed in this paper. It is found that CNN is very accurate for HDR but still there is a scope to improve the performance in terms of accuracy, complexity and timing.
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Yang, Ji Ying, Bei Zhang, and Yu Mao. "Study on Information Retrieval Sorting Algorithm in Network-Based Manufacturing Environment." Applied Mechanics and Materials 484-485 (January 2014): 183–86. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.183.

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The core problem of information retrieval is concentrated in the document for the user to retrieve the most relevant sub-set of documents, relying on sorting algorithms on the search results according to relevance sort, sorted the results as the user asked the query response information retrieval performance is determined by many factors, such as to query expressions quality index stemmer nonsense word disabled, query expansion technology, but fundamentally it is determined by the sort function sort function in some Standards document query indicates the degree of matching with the user, and accordingly to make a document with respect to the user's judgment, then the document in accordance with the degree of correlation with respect to the user in descending order, and returns the ordered list of documents as a result of the retrieval the pros and cons of the sorting algorithm directly affect the efficiency of the retrieval.
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Baranyi, Peter, Laszlo T. Koczy, and Tamas D. Gedeon. "Improved Fuzzy and Neural Network Algorithms for Word Frequency Prediction in Document Filtering." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 3 (June 20, 1998): 88–95. http://dx.doi.org/10.20965/jaciii.1998.p0088.

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With very large document collections or high-volume document streams of , finding relevant documents is a major information filtering problem. An aid to information retrieval systems produces a word frequency measure estimated from important parts of the document using neural network approaches. In this paper, a fuzzy logic technique and, as its simplified case, a neural network algorithm are proposed for this task. The comparison of these two and an alternative neural network algorithm are discussed.
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Tripathi, Kshitij, Rajendra G. Vyas, and Anil K. Gupta. "Document Classification Using Artificial Neural Network." Asian Journal of Computer Science and Technology 8, no. 2 (May 5, 2019): 55–58. http://dx.doi.org/10.51983/ajcst-2019.8.2.2140.

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The Document classification system is the field of data mining in which the format of data is based on bag of words (BoW) or document vector model and the task is to build a machine which after successfully learn the characteristic of given data set, predicts the category of the document to which the word vector belongs. In this approach document is represented by BoW where every single word is used as feature which occurs in a document. The proposed article presents artificial neural network approach which is hybrid of n-fold cross validation and training-validation-test approach for classification of data.
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Dissertations / Theses on the topic "Document network"

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Hasan, Mohammed Jaffer. "Document legalisation : a new approach to the document legalisation process using enterprise network technology." Thesis, Middlesex University, 2012. http://eprints.mdx.ac.uk/9875/.

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Documents issued in one country often have to be legalised (authenticated)before they can be used in another country. Different types of documents (legal papers) such as birth, death and marriage records, deeds of assignments, powers of attorney, commercial invoices etc. need to be legalised by the Destination Country before they can be assumed legal. Legalising a document simply means confirming that official documents are sealed and signed either with an Apostille Certificate for countries that are part of the Hague convention 1961, or with a Certificate of Authentication where countries are not party to The Hague Convention. Legalising (authenticating) documents is a process of verification of signatures. The aim of this research is to critically examine the current processes of document legalisation, through analysing and establishing the opportunities that lie before the organisation to implement a new process in document legalisation to replace the prolonged historical process currently used in some countries, specifically the United Arab Emirates (UAE). Using enterprise network technology1, this research will also produce a solution to the risks involved, the implementation and the security, and it will also analyse the impact of such implementation to the organisation. Considering the project, which explores a very sensitive area in the organisation and one of major change to the organisation’s business process, the authenticity of data must be given a high priority. Therefore, an online survey may not always be a legitimate approach. A paper survey may well fit the purpose but, on the other hand, a detailed interview and/ or telephone survey will be even more accurate. Hence I made use of a mixed method (qualitative/ quantitative) approach. The business of document legalisation goes back in history by more than two thousand years and, therefore, needs to be explored historically, establishing how the business of the document legalisation process has evolved alongside the established professions in government today, and defining the areas of concern such as security, availability, traceability and mobility. This will pave the way for an investigation to evaluate a new process that can utilise available technology to solve the areas of concern. The current process of Document Legalisation has been used for many years and a change in this process may take some time. There are many possible pitfalls that the programme may encounter, one of which is the change to a process that has not yet been established in any other area of the world, so there are no other occurrences in this subject for comparison. A clear and informative document explaining the project – a Specific, Measurable, Achievable, Realistic and Time Limit (SMART) description of the project – will solve any conflict. Considering that the research in th is complex topic runs in history for more than two thousand years, a mixed method approach should be used. However, to elaborate the methodology that can explore the underlying philosophical assumption taken by researchers a mixed methodology term should be more accurate, due to the history and composition of knowledge that have been accumulated in this topic. Hence clarification is needed to establish reasons and define a new approach in the document legalisation process. In addition to the historical literature, the main groups taken into consideration to form the data are the decision makers, interviews with senior staff and a survey for employees working in the field of document legalisation. To find reasons for every step in document legalisation, experiments should not be ignored. The reason for this is to clarify the area of data mismatch. The scope of the project will discuss the current risk involved in the current process of legalising documents, identifying its weaknesses, and the needs and requirements of the newly proposed process with recommendations to establish a solution utilising state of the art technology to provide a new secure, mobile and traceable process which is available 24/7.
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De, Bacco Caterina. "Decentralized network control, optimization and random walks on networks." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112164/document.

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Dans les dernières années, plusieurs problèmes ont été étudiés à l'interface entre la physique statistique et l'informatique. La raison étant que, souvent, ces problèmes peuvent être réinterprétés dans le langage de la physique des systèmes désordonnés, où un grand nombre de variables interagit à travers champs locales qui dépendent de l'état du quartier environnant. Parmi les nombreuses applications de l'optimisation combinatoire le routage optimal sur les réseaux de communication est l'objet de la première partie de la thèse. Nous allons exploiter la méthode de la cavité pour formuler des algorithmes efficaces de type ‘’message-passing’’ et donc résoudre plusieurs variantes du problème grâce à sa mise en œuvre numérique. Dans un deuxième temps, nous allons décrire un modèle pour approcher la version dynamique de la méthode de la cavité, ce qui permet de diminuer la complexité du problème de l'exponentielle de polynôme dans le temps. Ceci sera obtenu en utilisant le formalisme de ‘’Matrix Product State’’ de la mécanique quantique.Un autre sujet qui a suscité beaucoup d'intérêt en physique statistique de processus dynamiques est la marche aléatoire sur les réseaux. La théorie a été développée depuis de nombreuses années dans le cas que la topologie dessous est un réseau de dimension d. Au contraire le cas des réseaux aléatoires a été abordé que dans la dernière décennie, laissant de nombreuses questions encore ouvertes pour obtenir des réponses. Démêler plusieurs aspects de ce thème fera l'objet de la deuxième partie de la thèse. En particulier, nous allons étudier le nombre moyen de sites distincts visités au cours d'une marche aléatoire et caractériser son comportement en fonction de la topologie du graphe. Enfin, nous allons aborder les événements rares statistiques associées aux marches aléatoires sur les réseaux en utilisant le ‘’Large deviations formalism’’. Deux types de transitions de phase dynamiques vont se poser à partir de simulations numériques. Nous allons conclure décrivant les principaux résultats d'une œuvre indépendante développée dans le cadre de la physique hors de l'équilibre. Un système résoluble en deux particules browniens entouré par un bain thermique sera étudiée fournissant des détails sur une interaction à médiation par du bain résultant de la présence du bain
In the last years several problems been studied at the interface between statistical physics and computer science. The reason being that often these problems can be reinterpreted in the language of physics of disordered systems, where a big number of variables interacts through local fields dependent on the state of the surrounding neighborhood. Among the numerous applications of combinatorial optimisation the optimal routing on communication networks is the subject of the first part of the thesis. We will exploit the cavity method to formulate efficient algorithms of type message-passing and thus solve several variants of the problem through its numerical implementation. At a second stage, we will describe a model to approximate the dynamic version of the cavity method, which allows to decrease the complexity of the problem from exponential to polynomial in time. This will be obtained by using the Matrix Product State formalism of quantum mechanics. Another topic that has attracted much interest in statistical physics of dynamic processes is the random walk on networks. The theory has been developed since many years in the case the underneath topology is a d-dimensional lattice. On the contrary the case of random networks has been tackled only in the past decade, leaving many questions still open for answers. Unravelling several aspects of this topic will be the subject of the second part of the thesis. In particular we will study the average number of distinct sites visited during a random walk and characterize its behaviour as a function of the graph topology. Finally, we will address the rare events statistics associated to random walks on networks by using the large-deviations formalism. Two types of dynamic phase transitions will arise from numerical simulations, unveiling important aspects of these problems. We will conclude outlining the main results of an independent work developed in the context of out-of-equilibrium physics. A solvable system made of two Brownian particles surrounded by a thermal bath will be studied providing details about a bath-mediated interaction arising for the presence of the bath
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Li, Yue. "Edge computing-based access network selection for heterogeneous wireless networks." Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S042/document.

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Au cours de ces dernières décennies, les réseaux de télécommunications mobiles ont évolué de la 1G à la 4G. La 4G permet la coexistence de différents réseaux d'accès. Ainsi, les utilisateurs ont la capacité de se connecter à un réseau hétérogène, constitué de plusieurs réseaux d'accès. Toutefois, la sélection du réseau approprié n'est pas une tâche facile pour les utilisateurs mobiles puisque les conditions de chaque réseau d'accès changent rapidement. Par ailleurs, en termes d'usage, le streaming vidéo devient le service principal de transfert de données sur les réseaux mobiles, ce qui amène les fournisseurs de contenu et les opérateurs de réseau à coopérer pour garantir la qualité de la diffusion. Dans ce contexte, la thèse propose la conception d'une approche novatrice pour la prise de décision optimale de sélection de réseau et une architecture améliorant les performances des services de streaming adaptatif dans un réseau hétérogène. En premier lieu, nous introduisons un modèle analytique décrivant la procédure de sélection de réseau en ne considérant déjà qu'une seule classe de trafic. Nous concevons ensuite une stratégie de sélection basée sur des fondements de la théorie du contrôle optimal linéaire. Des simulations sous MATLAB sont effectuées pour valider l'efficacité du mécanisme proposé. Sur ce même principe, nous étendons ce modèle avec un modèle analytique général décrivant les procédures de sélection de réseau dans des environnements de réseaux hétérogènes avec de multiples classes de trafic. Le modèle proposé est ensuite utilisé pour dériver un mécanisme adaptatif basé sur la théorie du contrôle, qui permet non seulement d'aider à piloter dynamiquement le trafic vers l'accès réseau le plus approprié mais aussi de bloquer dynamiquement le trafic résiduel lorsque le réseau est congestionné en ajustant les probabilités d'accès optimales. Nous discutons aussi les avantages d'une intégration transparente du mécanisme proposé avec l'ANDSF, solution fonctionnelle normalisée pour la sélection de réseau. Un prototype est également implémenté dans ns-3. En second lieu, nous nous concentrons sur l'amélioration des performances de DASH pour les utilisateurs mobiles dans un environnement de réseau d'accès 4G uniquement. Nous introduisons une nouvelle architecture basée sur l'utilisation de serveurs distribués en périphérie de réseau suivant le standard MEC. Le mécanisme d'adaptation proposé, fonctionnant en tant que service MEC, peut modifier les fichiers de manifeste en temps réel, en réponse à la congestion du réseau et à la demande dynamique de flux de streaming. Ces modifications conduisent ainsi les clients à sélectionner des représentations vidéo de débit / qualité plus appropriées. Nous avons développé une plateforme de test virtualisée pour l'expérimentation de notre proposition. Les résultats ainsi obtenus démontrent ses avantages en terme de QoE comparés aux approches d'adaptation traditionnelles, purement pilotées par les clients, car notre approche améliore non seulement le MOS mais aussi l'équité face à la congestion. Enfin, nous étendons l'architecture proposée basée sur MEC pour supporter le service de streaming adaptatif DASH dans un réseau hétérogène multi-accès afin de maximiser la QoE et l'équité des utilisateurs mobiles. Dans ce scénario, notre mécanisme doit aider les utilisateurs à sélectionner la qualité vidéo et le réseau et nous le formulons comme un problème d'optimisation. Ce problème d'optimisation peut être résolu par l'outil IBM CPLEX, mais cela prend du temps et ne peut être envisagé à grande échelle. Par conséquent, nous introduisons une heuristique pour aborder la solution optimale avec moins de complexité. Ensuite, nous mettons en œuvre une expérimentation sur notre plateforme de tests. Le résultat démontre que, par rapport à l'outil IBM CPLEX, notre algorithme permet d'obtenir des performances similaires sur la QoE globale et l'équité, avec un gain de temps significatif
Telecommunication network has evolved from 1G to 4G in the past decades. One of the typical characteristics of the 4G network is the coexistence of heterogeneous radio access technologies, which offers end-users the capability to connect them and to switch between them with their mobile devices of the new generation. However, selecting the right network is not an easy task for mobile users since access network condition changes rapidly. Moreover, video streaming is becoming the major data service over the mobile network where content providers and network operators should cooperate to guarantee the quality of video delivery. In order to cope with this context, the thesis concerns the design of a novel approach for making an optimal network selection decision and architecture for improving the performance of adaptive streaming in the context of a heterogeneous network. Firstly, we introduce an analytical model (i.e. linear discrete-time system) to describe the network selection procedure considering one traffic class. Then, we consider the design of a selection strategy based on foundations from linear optimal control theory, with the objective to maximize network resource utilization while meeting the constraints of the supported services. Computer simulations with MATLAB are carried out to validate the efficiency of the proposed mechanism. Based on the same principal we extend this model with a general analytical model describing the network selection procedures in heterogeneous network environments with multiple traffic classes. The proposed model was, then, used to derive a scalable mechanism based on control theory, which allows not only to assist in steering dynamically the traffic to the most appropriate network access but also helps in blocking the residual traffic dynamically when the network is congested by adjusting dynamically the access probabilities. We discuss the advantages of a seamless integration with the ANDSF. A prototype is also implemented into ns-3. Simulation results sort out that the proposed scheme prevents the network congestion and demonstrates the effectiveness of the controller design, which can maximize the network resources allocation by converging the network workload to the targeted network occupancy. Thereafter, we focus on enhancing the performance of DASH in a mobile network environment for the users which has one access network. We introduce a novel architecture based on MEC. The proposed adaptation mechanism, running as an MEC service, can modify the manifest files in real time, responding to network congestion and dynamic demand, thus driving clients towards selecting more appropriate quality/bitrate video representations. We have developed a virtualized testbed to run the experiment with our proposed scheme. The simulation results demonstrate its QoE benefits compared to traditional, purely client-driven, bitrate adaptation approaches since our scheme notably improves both on the achieved MOS and on fairness in the face of congestion. Finally, we extend the proposed the MEC-based architecture to support the DASH service in a multi-access heterogeneous network in order to maximize the QoE and fairness of mobile users. In this scenario, our scheme should help users select both video quality and access network and we formulate it as an optimization problem. This optimization problem can be solved by IBM CPLEX tool. However, this tool is time-consuming and not scalable. Therefore, we introduce a heuristic algorithm to make a sub-optimal solution with less complexity. Then we implement a testbed to conduct the experiment and the result demonstrates that our proposed algorithm notably can achieve similar performance on overall achieved QoE and fairness with much more time-saving compared to the IBM CPLEX tool
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Benfattoum, Youghourta. "Network coding for quality of service in wireless multi-hop networks." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA112267/document.

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Dans cette thèse, nous nous intéressons à l’application du codage réseau pour garantir la qualité de service (QoS) dans les réseaux sans fil multi-sauts. Comme le support de transmission est partagé, les réseaux sans fil souffrent de l’impact négatif des interférences sur la bande passante. Il est alors intéressant de proposer une approche basée sur le codage réseau qui prenne en compte ces interférences durant le processus de routage. Dans ce contexte, nous proposons d’abord un algorithme minimisant l’impact des interférences pour des flux unicast tout en respectant la bande passante qu’ils exigent. Puis, nous le combinons avec le codage réseau afin d’augmenter le nombre des flux acceptés et avec le contrôle de topologie pour améliorer davantage la gestion des interférences. Nous montrons par simulation l’intérêt de combiner les trois domaines : codage réseau, gestion des interférences et contrôle de topologie. Nous abordons également la gestion du délai pour les flux multicast et utilisons le codage réseau basé sur les générations (GBNC) qui combine les paquets par bloc. La plupart des travaux portant sur le GBNC considèrent une taille de génération fixe mais à cause des variations de l’état du réseau le délai de décodage et de récupération du bloc de paquets peut varier, dégradant la QoS. Pour résoudre ce problème, nous proposons une méthode qui ajuste la taille de la génération de façon dynamique pour respecter un certain délai de décodage avec prise en compte des contextes réseau et contenu. De plus, nous améliorons notre approche pour contrecarrer les pertes des acquittements. Puis, nous proposons de l’utiliser dans un réseau de domicile pour la diffusion de vidéo à la demande. Notre solution améliore la QoS et la qualité d’expérience pour l’utilisateur final sans équipement additionnel. Finalement, nous abordons un sujet plus théorique dans lequel nous présentons un nouveau réseau basé sur le schéma Butterfly pour des flux multi-sources multi-destinations. Nous caractérisons la taille du buffer du nœud source en utilisant la théorie des files d’attente et montrons qu’elle correspond aux résultats de simulation
In this thesis we deal with the application of Network Coding to guarantee the Quality of Service (QoS) for wireless multi-hop networks. Since the medium is shared, wireless networks suffer from the negative interference impact on the bandwidth. It is thus interesting to propose a Network Coding based approach that takes into account this interference during the routing process. In this context, we first propose an algorithm minimizing the interference impact for unicast flows while respecting their required bandwidth. Then, we combine it with Network Coding to increase the number of admitted flows and with Topology Control to still improve the interference management. We show by simulation the benefit of combining the three fields: Network Coding, interference consideration and Topology Control. We also deal with delay management for multicast flows and use the Generation-Based Network Coding (GBNC) that combines the packets per blocks. Most of the works on GBNC consider a fixed generation size. Because of the network state variations, the delay of decoding and recovering a block of packets can vary accordingly degrading the QoS. To solve this problem, we propose a network-and content-aware method that adjusts the generation size dynamically to respect a certain decoding delay. We also enhance it to overcome the issue of acknowledgement loss. We then propose to apply our approach in a Home Area Network for Live TV and video streaming. Our solution provides QoS and Quality of Experience for the end user with no additional equipment. Finally, we focus on a more theoretical work in which we present a new Butterfly-based network for multi-source multi-destination flows. We characterize the source node buffer size using the queuing theory and show that it matches the simulation results
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Varloot, Rémi. "Dynamic network formation." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEE048/document.

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Cette thèse porte sur la rapidité du temps de mélange de chaînes de Markov sur des graphes. La contribution principale concerne les graphes avec des dynamiques locales sur les arêtes, la topologie du graphe évoluant au fur et à mesure que les arêtes glissent les unes le long des autres. Nous proposons une classification des différents modèles existants de graphes dynamiques, tout en illustrant l’importance des transitions le long d’une structure mouvante pour améliorer la vitesse de convergence. Cette étude est complétée par la preuve, pour l’une de ces dynamiques, d’un temps de mélange rapide. Nous définissons notamment l’expansion partielle d’un graphe. Celle-ci permet de suivre l’avancement de la dynamique, partant d’un état de faible expansion, jusqu’à obtention d’une bonne expansion à l’équilibre. La fin de cette thèse porte sur une amélioration de l’algorithme de simulation parfaite de Propp et Wilson. Nous introduisant un oracle pour les transitions, inspiré de l’échantillonnage préférentiel, qui permet de réduire la complexité de l’algorithme. Nous fournissons une preuve de correction, ainsi qu’une étude de l’impact de cette méthode sur la vitesse d’échantillonnage d’ensembles indépendants pour certains graphes
This thesis focuses on the rapid mixing of graph-related Markov chains. The main contribution concerns graphs with local edge dynamics, in which the topology of a graph evolves as edges slide along one another. We propose a classification of existing models of dynamic graphs, and illustrate how evolving along a changing structure improves the convergence rate. This is complemented by a proof of the rapid mixing time for one such dynamic. As part of this proof, we introduce the partial expansion of a graph. This notion allows us to track the progression of the dynamic, from a state with poor expansion to good expansion at equilibrium. The end of the thesis proposes an improvement of the Propp and Wilson perfect sampling technique. We introduce oracle sampling, a method inspired by importance sampling that reduces the overall complexity of the Propp and Wilson algorithm. We provide a proof of correctness, and study the performance of this method when sampling independent sets from certain graphs
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Blein, Florent. "Automatic Document Classification Applied to Swedish News." Thesis, Linköping University, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-3065.

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The first part of this paper presents briefly the ELIN[1] system, an electronic newspaper project. ELIN is a framework that stores news and displays them to the end-user. Such news are formatted using the xml[2] format. The project partner Corren[3] provided ELIN with xml articles, however the format used was not the same. My first task has been to develop a software that converts the news from one xml format (Corren) to another (ELIN).

The second and main part addresses the problem of automatic document classification and tries to find a solution for a specific issue. The goal is to automatically classify news articles from a Swedish newspaper company (Corren) into the IPTC[4] news categories.

This work has been carried out by implementing several classification algorithms, testing them and comparing their accuracy with existing software. The training and test documents were 3 weeks of the Corren newspaper that had to be classified into 2 categories.

The last tests were run with only one algorithm (Naïve Bayes) over a larger amount of data (7, then 10 weeks) and categories (12) to simulate a more real environment.

The results show that the Naïve Bayes algorithm, although the oldest, was the most accurate in this particular case. An issue raised by the results is that feature selection improves speed but can seldom reduce accuracy by removing too many features.

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Tsai, Chun-I. "A Study on Neural Network Modeling Techniques for Automatic Document Summarization." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-395940.

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With the Internet becoming widespread, countless articles and multimedia content have been filled in our daily life. How to effectively acquire the knowledge we seek becomes one of the unavoidable issues. To help people to browse the main theme of the document faster, many studies are dedicated to automatic document summarization, which aims to condense one or more documents into a short text yet still keep its essential content as much as possible. Automatic document summarization can be categorized into extractive and abstractive. Extractive summarization selects the most relevant set of sentences to a target ratio and assemble them into a concise summary. On the other hand, abstractive summarization produces an abstract after understanding the key concept of a document. The recent past has seen a surge of interest in developing deep neural network-based supervised methods for both types of automatic summarization. This thesis presents a continuation of this line and exploit two kinds of frameworks, which integrate convolutional neural network (CNN), long short-term memory (LSTM) and multilayer perceptron (MLP) for extractive speech summarization. The empirical results seem to demonstrate the effectiveness of neural summarizers when compared with other conventional supervised methods. Finally, to further explore the ability of neural networks, we experiment and analyze the results of applying sequence-to-sequence neural networks for abstractive summarization.
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Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066549/document.

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Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RAN
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost
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Mangili, Michele. "Efficient in-network content distribution : wireless resource sharing, network planning, and security." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLS182/document.

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Au cours de ces dernières années, la quantité de trafic que les utilisateurs Internet produisent sur une base quotidienne a augmenté de façon exponentielle, principalement en raison du succès des services de streaming vidéo, tels que Netflix et YouTube. Alors que les réseaux de diffusion de contenu (Content-Delivery Networks, CDN) sont la technique standard utilisée actuellement pour servir les demandes des utilisateurs, la communauté scientifique a formulé des propositions connues sous le nom de Content-Centric Networks (CCN) pour changer la pile de protocoles réseau afin de transformer Internet en une infrastructure de distribution de contenu. Dans ce contexte, cette thèse de doctorat étudie des techniques efficaces pour la distribution de contenu numérique en tenant compte de trois problèmes complémentaires : 1) Nous considérons le scénario d’un réseau hétérogène sans fil, et nous formulons un mécanisme pour motiver les propriétaires des points d’accès à partager leur capacité WiFi et stockage cache inutilisés, en échange d’une contribution économique.2) Nous étudions le problème centralisé de planification du réseau en présence de caches distribuées et (I) nous analysons la migration optimale du réseau à CCN; (II) nous comparons les bornes de performance d’un réseau CDN avec ceux d’un CCN, et (III) nous considérons un réseau CDN virtualisé et étudions le problème stochastique de planification d’une telle infrastructure.3) Nous considérons les implications de sécurité sur le contrôle d’accès et la traçabilité, et nous formulons ConfTrack-CCN, une extension deCCN utilisée pour garantir la confidentialité, traçabilité et l’évolution de la politique d’accès, en présence de caches distribuées
In recent years, the amount of traffic requests that Internet users generate on a daily basis has increased exponentially, mostly due to the worldwide success of video streaming services, such as Netflix and YouTube. While Content-Delivery Networks (CDNs) are the de-facto standard used nowadays to serve the ever increasing users’ demands, the scientific community has formulated proposals known under the name of Content-Centric Networks (CCN) to change the network protocol stack in order to turn the network into a content distribution infrastructure. In this context this Ph.D. thesis studies efficient techniques to foster content distribution taking into account three complementary problems:1) We consider the scenario of a wireless heterogeneous network, and we formulate a novel mechanism to motivate wireless access point owners to lease their unexploited bandwidth and cache storage, in exchange for an economic incentive.2) We study the centralized network planning problem and (I) we analyze the migration to CCN; (II) we compare the performance bounds for a CDN with those of a CCN, and (III) we take into account a virtualized CDN and study the stochastic planning problem for one such architecture.3) We investigate the security properties on access control and trackability and formulate ConfTrack-CCN: a CCN extension to enforce confidentiality, trackability and access policy evolution in the presence of distributed caches
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Macpherson, Janet Robertson. "Implications of the inclusion of document retrieval systems as actors in a social network." Thesis, University of North Texas, 2005. https://digital.library.unt.edu/ark:/67531/metadc4913/.

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Traditionally, social network analysis (SNA) techniques enable the examination of relationships and the flow of information within networks of human members or groups of humans. This study extended traditional social network analysis to include a nonhuman group member, specifically a document retrieval system. The importance of document retrieval systems as information sources, the changes in business environments that necessitates the use of information and communication technologies, and the attempts to make computer systems more life-like, provide the reasons for considering the information system as a group member. The review of literature for this study does not encompass a single body of knowledge. Instead, several areas combined to inform this study, including social informatics for its consideration of the intersection of people and information technology, network theory and social network analysis, organizations and information, organizational culture, and finally, storytelling in organizations as a means of transferring information. The methodology included distribution of surveys to two small businesses that used the same document retrieval system, followed by semi-structured interviews of selected group members, which allowed elaboration on the survey findings. The group members rated each other and the system on four interaction criteria relating to four social networks of interest, including awareness, access, information flow, and problem solving. Traditional measures of social networks, specifically density, degree, reciprocity, transitivity, distance, degree centrality, and closeness centrality provided insight into the positioning of the nonhuman member within the social group. The human members of the group were able to respond to the survey that included the system but were not ready to consider the system as being equivalent to other human members. SNA measures positioned the system as an average member of the group, not a star, but not isolated either. Examination of the surveys or the interviews in isolation would not have given a complete picture of the system's place within the group.
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Books on the topic "Document network"

1

Computer Systems Laboratory (U.S.), ed. Open document architecture (ODA) raster document application profile (DAP). Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, Computer Systems Laboratory, 1995.

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Carr, Richard. Document interchange. London: DISC, BSi Standards, 1992.

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Alemna, Anaba A. The Ghana Interlibrary Lending and Document Delivery Network (GILLDDNET). Oxford: International Network for the Availability of Scientific Publications (INASP), 2004.

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Gelaw, Bantayehu. Maize and Wheat Improvement Network for SADCC: Project document. [Gaborone]: SACCAR, 1991.

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Appelt, Wolfgang. Document architecture in open systems: The ODA standard. Berlin: Springer-Verlag, 1992.

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Copeland, Lynn. British Columbia: Electronic library network, OJAC project : final report. [Burnaby, B.C: s.n.], 1993.

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Bloch, Cecil. Geo-referenced information network external design: Data design, document A (revision 3). Mountain View, Calif. (1200 Villa St., Mountain View 94041-1100): Research Libraries Group, 1988.

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K, Besler Steven, and Mallais Sacha, eds. Webmaster's guide to Internet server connectivity. Indianapolis, IN: New Riders Pub, 1996.

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Library of Congress. Network Development and MARC Standards Office., ed. Riding the electronic wave--document delivery: Proceedings of the Library of Congress Network Advisory Committee Meeting, November 29-December 1, 1989. Washington: Network Development and MARC Standards Office, Library of Congress, 1990.

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Mark, Ginsburg, ed. HTML and CGI unleashed. Indianapolis, IN: Sams Net, 1995.

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Book chapters on the topic "Document network"

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Esmark, Anders, and Peter Triantafillou. "Document Analysis of Network Topography and Network Programmes." In Methods in Democratic Network Governance, 99–124. London: Palgrave Macmillan UK, 2007. http://dx.doi.org/10.1057/9780230627468_5.

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Cho, Sung-Jung, and Jin Hyung Kim. "A Bayesian Network Approach for On-line Handwriting Recognition." In Digital Document Processing, 121–41. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-726-8_6.

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Li, Xiao-Hui, Fei Yin, and Cheng-Lin Liu. "Page Segmentation Using Convolutional Neural Network and Graphical Model." In Document Analysis Systems, 231–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57058-3_17.

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Voerman, Joris, Aurélie Joseph, Mickael Coustaty, Vincent Poulain d’Andecy, and Jean-Marc Ogier. "Evaluation of Neural Network Classification Systems on Document Stream." In Document Analysis Systems, 262–76. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57058-3_19.

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Kim, Sung Wan, Pan Seop Shin, Youn Hee Kim, Jaeho Lee, and Hae Chull Lim. "A Data Model and Algebra for Document-Centric XML Document." In Information Networking: Wireless Communications Technologies and Network Applications, 714–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45801-8_67.

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Li, Nan, Qianyi Jiang, Qi Song, Rui Zhang, and Xiaolin Wei. "ALEC: An Accurate, Light and Efficient Network for CAPTCHA Recognition." In Document Analysis Systems, 60–73. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57058-3_5.

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Wijaya, Dimaz Ankaa, Joseph K. Liu, Ron Steinfeld, Dongxi Liu, Fengkie Junis, and Dony Ariadi Suwarsono. "Designing Smart Contract for Electronic Document Taxation." In Cryptology and Network Security, 199–213. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31578-8_11.

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Yoshikoshi, Masahiro, Kenji Matsunaga, and Kyoko Yoshida. "A Personal Document Network Building System for Digital Document Searches." In Communications in Computer and Information Science, 458–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39476-8_93.

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Xie, Guo-Wang, Fei Yin, Xu-Yao Zhang, and Cheng-Lin Liu. "Dewarping Document Image by Displacement Flow Estimation with Fully Convolutional Network." In Document Analysis Systems, 131–44. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57058-3_10.

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Stuart, Ian, Sung-Hyuk Cha, and Charles Tappert. "A Neural Network Classifier for Junk E-Mail." In Document Analysis Systems VI, 442–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-28640-0_42.

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Conference papers on the topic "Document network"

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Wu, Hao, and Kristina Lerman. "Deep Context: A Neural Language Model for Large-scale Networked Documents." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/431.

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We propose a scalable neural language model that leverages the links between documents to learn the deep context of documents. Our model, Deep Context Vector, takes advantage of distributed representations to exploit the word order in document sentences, as well as the semantic connections among linked documents in a document network. We evaluate our model on large-scale data collections that include Wikipedia pages, and scientific and legal citations networks. We demonstrate its effectiveness and efficiency on document classification and link prediction tasks.
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Gou, Liang, Xiaolong (Luke) Zhang, Hung-Hsuan Chen, Jung-Hyun Kim, and C. Lee Giles. "Social network document ranking." In the 10th annual joint conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1816123.1816170.

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Zhao, Xueliang, Chongyang Tao, Wei Wu, Can Xu, Dongyan Zhao, and Rui Yan. "A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/756.

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We present a document-grounded matching network (DGMN) for response selection that can power a knowledge-aware retrieval-based chatbot system. The challenges of building such a model lie in how to ground conversation contexts with background documents and how to recognize important information in the documents for matching. To overcome the challenges, DGMN fuses information in a document and a context into representations of each other, and dynamically determines if grounding is necessary and importance of different parts of the document and the context through hierarchical interaction with a response at the matching step. Empirical studies on two public data sets indicate that DGMN can significantly improve upon state-of-the-art methods and at the same time enjoys good interpretability.
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Tian, Bing, Yong Zhang, Jin Wang, and Chunxiao Xing. "Hierarchical Inter-Attention Network for Document Classification with Multi-Task Learning." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/495.

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Document classification is an essential task in many real world applications. Existing approaches adopt both text semantics and document structure to obtain the document representation. However, these models usually require a large collection of annotated training instances, which are not always feasible, especially in low-resource settings. In this paper, we propose a multi-task learning framework to jointly train multiple related document classification tasks. We devise a hierarchical architecture to make use of the shared knowledge from all tasks to enhance the document representation of each task. We further propose an inter-attention approach to improve the task-specific modeling of documents with global information. Experimental results on 15 public datasets demonstrate the benefits of our proposed model.
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Le, Tuan M. V., and Hady W. Lauw. "Probabilistic Latent Document Network Embedding." In 2014 IEEE International Conference on Data Mining (ICDM). IEEE, 2014. http://dx.doi.org/10.1109/icdm.2014.119.

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Rucklidge, William J., and Daniel P. Huttenlocher. "Flexible network document imaging architecture." In Electronic Imaging, edited by Giordano B. Beretta and Raimondo Schettini. SPIE, 1999. http://dx.doi.org/10.1117/12.373447.

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Nicula, Bogdan, Cecile A. Perret, Mihai Dascalu, and Danielle S. McNamara. "Multi-document Cohesion Network Analysis: Automated Prediction of Inferencing across Multiple Documents." In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2020. http://dx.doi.org/10.1109/ictai50040.2020.00061.

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Kim, Minkyoung, Byoung-Tak Zhang, and June-Sup Lee. "Subjective Document Classification Using Network Analysis." In 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2010). IEEE, 2010. http://dx.doi.org/10.1109/asonam.2010.65.

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Pimparkar, Kaustubh, Rahul Lulla, Pratik Rathod, V. Anirudh, and Suruchi G. Dedgaonkar. "Document Management using Artificial Neural Network." In 2019 International Conference on Communication and Electronics Systems (ICCES). IEEE, 2019. http://dx.doi.org/10.1109/icces45898.2019.9002062.

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Balasundaram, Kirusiha, and C. R. J. Amalraj. "Speech Document Summarization using Neural Network." In 2019 4th International Conference on Information Technology Research (ICITR). IEEE, 2019. http://dx.doi.org/10.1109/icitr49409.2019.9407785.

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Reports on the topic "Document network"

1

Searl, Leon S., Ed Komp, Dan DePardo, Dan Deavours, and Martin Kuehnhausen. SensorNet 3 Requirements Document: Container Transportation Security Network. Fort Belvoir, VA: Defense Technical Information Center, January 2011. http://dx.doi.org/10.21236/ada539046.

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Chassin, David P. GridLAB-D Technical Support Document: Network Module Version 1.0. Office of Scientific and Technical Information (OSTI), May 2008. http://dx.doi.org/10.2172/939870.

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García-Mantilla, Daniel. PLAC Network Best Practices Series: Target-Income Design of Incentives, Benchmark Portfolios and Performance Metrics for Pension Funds. Inter-American Development Bank, June 2021. http://dx.doi.org/10.18235/0003599.

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In defined contribution systems, at the end of the accumulation phase the assets in the retirement account are exchanged for a pension. The conversion rate from assets to retirement income (which depends on the level of interest rates) is very volatile, and its variations constitute the main investment risk facing pension fund affiliates. In this sense, performance metrics, management fees and benchmark portfolios that focus on assets (and asset returns) and ignore the variations in the conversion rate, embed several problems: i. they send wrong signals to regulators, fund managers and workers, ii. they provide wrong incentives to pension fund management companies, and iii. they leave pension fund affiliates exposed to their largest risk factor, even during the last few years preceding their retirement date. We find that regulatory incentives with these fundamental problems are ubiquitous in the region. The document presents a series of best practices, and delivers a practical set of tools to assist regulators and supervisors in designing a framework that improves security and sufficiency of retirement income, and provides relevant and timely information to pension fund affiliates. The framework achieves that by fostering an integration of the accumulation and the payout phases, and an alignment of the regulatory incentives for pension fund management companies with the retirement income objectives of pension fund affiliates. Using historical data from Colombia as a case study, the document illustrates and quantifies the improvements in terms of pension benefits and retirement income security that the proposed framework could bring.
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Dinkel, Charles. Secure data network system (SDNS) access control documents. Gaithersburg, MD: National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.ir.90-4259.

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Dinkel, Charles. Secure Data Network System (SDNS) key management documents. Gaithersburg, MD: National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.ir.90-4262.

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Voegtlin, David. The Suction Trap Network Documents Soybean Aphid Migrations. Ames: Iowa State University, Digital Repository, 2011. http://dx.doi.org/10.31274/farmprogressreports-180814-542.

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Voegtlin, David. The Suction Trap Network Documents Soybean Aphid Migrations. Ames: Iowa State University, Digital Repository, 2011. http://dx.doi.org/10.31274/farmprogressreports-180814-2480.

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Dudley, G. APPN/HPR in IP Networks APPN Implementers' Workshop Closed Pages Document. RFC Editor, May 1998. http://dx.doi.org/10.17487/rfc2353.

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Ashcroft, John. Evaluation of Updates to the Risk-based Supervision Model of the Superintendence of Pensions in Chile. Inter-American Development Bank, June 2017. http://dx.doi.org/10.18235/0003446.

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This first document of the PLAC Network Technical Assistance Document Series, entitled “Evaluation of Updates to the Risk-Based Supervision Model of the Superintendence of Pensions in Chile”, provides a commentary on the actions taken by the Superintendence of Pensions in response to the original advisory report on the application of risk-based supervision, which was formally delivered in December 2016. This revised version of the report also takes into account discussions with managers and staff from the Superintendence of Pensions during a series of presentations and training workshops held in Santiago de Chile during the week of 12-16 June 2017.
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Robles, Edgar A. Haiti Pension System: Recommendations to Improve the Regulation. Inter-American Development Bank, March 2018. http://dx.doi.org/10.18235/0003598.

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This tenth document of the PLAC Network Technical Assistance Document Series, entitled “Haiti pension system - Recommendations to improve the regulation”, provides general recommendations for the regulatory framework of the pension system in Haiti and tries to identify broad key policy options to improve the performance of the pension system. The policies are directed to strengthen and harmonize the rules of governance for the Office Nationale d'Assurance-Vieillesse (ONA), which covers private salaried workers, and the Plan de Retraite de l'Administration Publique (PRAP), to increase their capacity to manage risks, facilitate supervision of pension funds, improve sustainability, adequacy and equity, and establish guidelines for investments policies.
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