Learning structure and schemas from heterogeneous domains in networked systems: a survey

The rapidly growing amount of available digital documents of various formats and the possibility to access these through internet-based technologies in distributed environments, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Specifically, the extremely large size of document collections make it impossible to manually organize such documents. Additionally, most of the document sexist in an unstructured form and do not follow any schemas. Therefore, research efforts in this direction are being dedicated to automatically infer structure and schemas. This is essential in order to better organize huge collections as well as to effectively and efficiently retrieve documents in heterogeneous domains in networked system. This paper presents a survey of the state-of-the-art methods for inferring structure from documents and schemas in networked environments. The survey is organized around the most important application domains, namely, bio-informatics, sensor networks, social networks, P2Psystems, automation and control, transportation and privacy preserving for which we analyze the recent developments on dealing with unstructured data in such domains.Peer ReviewedPostprint (published version

Contributions to security and privacy protection in recommendation systems

A recommender system is an automatic system that, given a customer model and a set of available documents, is able to select and offer those documents that are more interesting to the customer. From the point of view of security, there are two main issues that recommender systems must face: protection of the users' privacy and protection of other participants of the recommendation process. Recommenders issue personalized recommendations taking into account not only the profile of the documents, but also the private information that customers send to the recommender. Hence, the users' profiles include personal and highly sensitive information, such as their likes and dislikes. In order to have a really useful recommender system and improve its efficiency, we believe that users shouldn't be afraid of stating their preferences. The second challenge from the point of view of security involves the protection against a new kind of attack. Copyright holders have shifted their targets to attack the document providers and any other participant that aids in the process of distributing documents, even unknowingly. In addition, new legislation trends such as ACTA or the ¿Sinde-Wert law¿ in Spain show the interest of states all over the world to control and prosecute these intermediate nodes. we proposed the next contributions: 1.A social model that captures user's interests into the users' profiles, and a metric function that calculates the similarity between users, queries and documents. This model represents profiles as vectors of a social space. Document profiles are created by means of the inspection of the contents of the document. Then, user profiles are calculated as an aggregation of the profiles of the documents that the user owns. Finally, queries are a constrained view of a user profile. This way, all profiles are contained in the same social space, and the similarity metric can be used on any pair of them. 2.Two mechanisms to protect the personal information that the user profiles contain. The first mechanism takes advantage of the Johnson-Lindestrauss and Undecomposability of random matrices theorems to project profiles into social spaces of less dimensions. Even if the information about the user is reduced in the projected social space, under certain circumstances the distances between the original profiles are maintained. The second approach uses a zero-knowledge protocol to answer the question of whether or not two profiles are affine without leaking any information in case of that they are not. 3.A distributed system on a cloud that protects merchants, customers and indexers against legal attacks, by means of providing plausible deniability and oblivious routing to all the participants of the system. We use the term DocCloud to refer to this system. DocCloud organizes databases in a tree-shape structure over a cloud system and provide a Private Information Retrieval protocol to avoid that any participant or observer of the process can identify the recommender. This way, customers, intermediate nodes and even databases are not aware of the specific database that answered the query. 4.A social, P2P network where users link together according to their similarity, and provide recommendations to other users in their neighborhood. We defined an epidemic protocol were links are established based on the neighbors similarity, clustering and randomness. Additionally, we proposed some mechanisms such as the use SoftDHT to aid in the identification of affine users, and speed up the process of creation of clusters of similar users. 5.A document distribution system that provides the recommended documents at the end of the process. In our view of a recommender system, the recommendation is a complete process that ends when the customer receives the recommended document. We proposed SCFS, a distributed and secure filesystem where merchants, documents and users are protectedEste documento explora c omo localizar documentos interesantes para el usuario en grandes redes distribuidas mediante el uso de sistemas de recomendaci on. Se de fine un sistema de recomendaci on como un sistema autom atico que, dado un modelo de cliente y un conjunto de documentos disponibles, es capaz de seleccionar y ofrecer los documentos que son m as interesantes para el cliente. Las caracter sticas deseables de un sistema de recomendaci on son: (i) ser r apido, (ii) distribuido y (iii) seguro. Un sistema de recomendaci on r apido mejora la experiencia de compra del cliente, ya que una recomendaci on no es util si es que llega demasiado tarde. Un sistema de recomendaci on distribuido evita la creaci on de bases de datos centralizadas con informaci on sensible y mejora la disponibilidad de los documentos. Por ultimo, un sistema de recomendaci on seguro protege a todos los participantes del sistema: usuarios, proveedores de contenido, recomendadores y nodos intermedios. Desde el punto de vista de la seguridad, existen dos problemas principales a los que se deben enfrentar los sistemas de recomendaci on: (i) la protecci on de la intimidad de los usuarios y (ii) la protecci on de los dem as participantes del proceso de recomendaci on. Los recomendadores son capaces de emitir recomendaciones personalizadas teniendo en cuenta no s olo el per l de los documentos, sino tambi en a la informaci on privada que los clientes env an al recomendador. Por tanto, los per les de usuario incluyen informaci on personal y altamente sensible, como sus gustos y fobias. Con el n de desarrollar un sistema de recomendaci on util y mejorar su e cacia, creemos que los usuarios no deben tener miedo a la hora de expresar sus preferencias. Para ello, la informaci on personal que est a incluida en los per les de usuario debe ser protegida y la privacidad del usuario garantizada. El segundo desafi o desde el punto de vista de la seguridad implica un nuevo tipo de ataque. Dado que la prevenci on de la distribuci on ilegal de documentos con derechos de autor por medio de soluciones t ecnicas no ha sido efi caz, los titulares de derechos de autor cambiaron sus objetivos para atacar a los proveedores de documentos y cualquier otro participante que ayude en el proceso de distribuci on de documentos. Adem as, tratados y leyes como ACTA, la ley SOPA de EEUU o la ley "Sinde-Wert" en España ponen de manfi esto el inter es de los estados de todo el mundo para controlar y procesar a estos nodos intermedios. Los juicios recientes como MegaUpload, PirateBay o el caso contra el Sr. Pablo Soto en España muestran que estas amenazas son una realidad

Contextual Social Networking

The thesis centers around the multi-faceted research question of how contexts may be detected and derived that can be used for new context aware Social Networking services and for improving the usefulness of existing Social Networking services, giving rise to the notion of Contextual Social Networking. In a first foundational part, we characterize the closely related fields of Contextual-, Mobile-, and Decentralized Social Networking using different methods and focusing on different detailed aspects. A second part focuses on the question of how short-term and long-term social contexts as especially interesting forms of context for Social Networking may be derived. We focus on NLP based methods for the characterization of social relations as a typical form of long-term social contexts and on Mobile Social Signal Processing methods for deriving short-term social contexts on the basis of geometry of interaction and audio. We furthermore investigate, how personal social agents may combine such social context elements on various levels of abstraction. The third part discusses new and improved context aware Social Networking service concepts. We investigate special forms of awareness services, new forms of social information retrieval, social recommender systems, context aware privacy concepts and services and platforms supporting Open Innovation and creative processes. This version of the thesis does not contain the included publications because of copyrights of the journals etc. Contact in terms of the version with all included publications: Georg Groh, [email protected] zentrale Gegenstand der vorliegenden Arbeit ist die vielschichtige Frage, wie Kontexte detektiert und abgeleitet werden können, die dazu dienen können, neuartige kontextbewusste Social Networking Dienste zu schaffen und bestehende Dienste in ihrem Nutzwert zu verbessern. Die (noch nicht abgeschlossene) erfolgreiche Umsetzung dieses Programmes führt auf ein Konzept, das man als Contextual Social Networking bezeichnen kann. In einem grundlegenden ersten Teil werden die eng zusammenhängenden Gebiete Contextual Social Networking, Mobile Social Networking und Decentralized Social Networking mit verschiedenen Methoden und unter Fokussierung auf verschiedene Detail-Aspekte näher beleuchtet und in Zusammenhang gesetzt. Ein zweiter Teil behandelt die Frage, wie soziale Kurzzeit- und Langzeit-Kontexte als für das Social Networking besonders interessante Formen von Kontext gemessen und abgeleitet werden können. Ein Fokus liegt hierbei auf NLP Methoden zur Charakterisierung sozialer Beziehungen als einer typischen Form von sozialem Langzeit-Kontext. Ein weiterer Schwerpunkt liegt auf Methoden aus dem Mobile Social Signal Processing zur Ableitung sinnvoller sozialer Kurzzeit-Kontexte auf der Basis von Interaktionsgeometrien und Audio-Daten. Es wird ferner untersucht, wie persönliche soziale Agenten Kontext-Elemente verschiedener Abstraktionsgrade miteinander kombinieren können. Der dritte Teil behandelt neuartige und verbesserte Konzepte für kontextbewusste Social Networking Dienste. Es werden spezielle Formen von Awareness Diensten, neue Formen von sozialem Information Retrieval, Konzepte für kontextbewusstes Privacy Management und Dienste und Plattformen zur Unterstützung von Open Innovation und Kreativität untersucht und vorgestellt. Diese Version der Habilitationsschrift enthält die inkludierten Publikationen zurVermeidung von Copyright-Verletzungen auf Seiten der Journals u.a. nicht. Kontakt in Bezug auf die Version mit allen inkludierten Publikationen: Georg Groh, [email protected]

MapReduce based RDF assisted distributed SVM for high throughput spam filtering

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityElectronic mail has become cast and embedded in our everyday lives. Billions of legitimate emails are sent on a daily basis. The widely established underlying infrastructure, its widespread availability as well as its ease of use have all acted as catalysts to such pervasive proliferation. Unfortunately, the same can be alleged about unsolicited bulk email, or rather spam. Various methods, as well as enabling architectures are available to try to mitigate spam permeation. In this respect, this dissertation compliments existing survey work in this area by contributing an extensive literature review of traditional and emerging spam filtering approaches. Techniques, approaches and architectures employed for spam filtering are appraised, critically assessing respective strengths and weaknesses. Velocity, volume and variety are key characteristics of the spam challenge. MapReduce (M/R) has become increasingly popular as an Internet scale, data intensive processing platform. In the context of machine learning based spam filter training, support vector machine (SVM) based techniques have been proven effective. SVM training is however a computationally intensive process. In this dissertation, a M/R based distributed SVM algorithm for scalable spam filter training, designated MRSMO, is presented. By distributing and processing subsets of the training data across multiple participating computing nodes, the distributed SVM reduces spam filter training time significantly. To mitigate the accuracy degradation introduced by the adopted approach, a Resource Description Framework (RDF) based feedback loop is evaluated. Experimental results demonstrate that this improves the accuracy levels of the distributed SVM beyond the original sequential counterpart. Effectively exploiting large scale, ‘Cloud’ based, heterogeneous processing capabilities for M/R in what can be considered a non-deterministic environment requires the consideration of a number of perspectives. In this work, gSched, a Hadoop M/R based, heterogeneous aware task to node matching and allocation scheme is designed. Using MRSMO as a baseline, experimental evaluation indicates that gSched improves on the performance of the out-of-the box Hadoop counterpart in a typical Cloud based infrastructure. The focal contribution to knowledge is a scalable, heterogeneous infrastructure and machine learning based spam filtering scheme, able to capitalize on collaborative accuracy improvements through RDF based, end user feedback. MapReduce based RDF Assisted Distributed SVM for High Throughput Spam Filterin

Actas da 10ª Conferência sobre Redes de Computadores

Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio

IDEAS-1997-2021-Final-Programs

This document records the final program for each of the 26 meetings of the International Database and Engineering Application Symposium from 1997 through 2021. These meetings were organized in various locations on three continents. Most of the papers published during these years are in the digital libraries of IEEE(1997-2007) or ACM(2008-2021)

Essential Speech and Language Technology for Dutch: Results by the STEVIN-programme

Computational Linguistics; Germanic Languages; Artificial Intelligence (incl. Robotics); Computing Methodologie

(Re)ordering and (dis)ordering of street trade:the case of Recife, Brazil

Informal urban street trade is a prevalent feature across the Global South where much of the production and/or buying and selling of goods and services is unregulated. For this reason, local authorities have historically seen it as backward, inefficient and detrimental to the development of urban areas and have thus developed formalisation programmes aimed to control and ultimately make it disappear. Critics argue that the design and implementation of these programmes can marginalise and disempower informal traders as it acts against the traders’ livelihoods and long-established practices they have developed for decades. This research speaks to these concerns and aims to investigate how informal urban street trade manages to continuously reproduce itself despite formalising efforts to make it vanish. The study follows a post-structuralist approach informed by post-development sensibilities (Escobar, 2011). The purpose is two-fold. First, to critically investigate the implications of imposed power-knowledge essentialism inherent to formalisation processes (Foucault, 1980). Second, to analyse the ways in which cultural and socioeconomic development is enacted through the daily assembling of informal urban street trade (Farías and Bender, 2012; McFarlane, 2011). The research offers a thick ethnographic inquiry, conducted over a one year-long period (2014-2015) in the urban centre of Recife, Northeast capital of Pernambuco state, Brazil. Recife is a particularly rich site to investigate these issues as informal urban street trade has historically been pervasive of its squares and streets and the municipally has in place a formalisation programme aimed to gather information about traders, license them and relocate them into purposefully-built facilities. The ethnographic inquiry focused on the practices, knowledges, materials and technologies associated with the daily work of both informal traders, selling on the streets, and governing officials implementing the formalisation programme, both on the streets and on the City Council office. Primary data collection was gathered through ethnographic observations and fieldnote diaries enriched with pictures and audio recordings of the day-to-day sensorial experience of informal urban street trade. This was enhanced with informal conversations as well as semi-structured and unstructured interviews with governing bodies’ officials, licenced and unlicensed street traders, formal shop owners, and a diversified set of urban citizens. The thesis highlights that formalisation, through the introduction of regulations, classification schemes and practices of classifying traders through an information system, seeks to establish and expand an individualistic developmentality among all actors. Through this, formalisation aims to shape and normalise their everyday practices to focus on the City Council’s agenda of rendering informal street trade as problematic and turning the solution of formalised trade not only unquestionable, but desirable by all. More problematically, the formalisation programme’s overdetermination of what a socioeconomic order is to be and its imposition of individualising subjectivities to assist in its implementation acts against the traders’ collective and community-based understanding of work and livelihoods which, contrary to the formalisation discourse, greatly benefit the cultural and socioeconomic development of these communities. This is achieved through the traders’ daily assembling of work, value and supply on the streets. The findings reveal that the collective organisation of traders’ work is strongly based on a ‘cooperative ethos’ that is not only efficient in taking advantage of and adapting to the challenging conditions of street markets, but also is key on the ongoing fostering and strengthening of the local community identity. The findings also show that traders, through their tacit knowledge of the best fits between products, services and sites, are key in shaping the valuation of both formal and informal enterprises as well as urban sites thus bolstering the local economy. Lastly, the findings also reveal that, through their interactions with formal and informal supply circuits, street traders are fundamental for the distribution and promotion of local artists and producers thus helping on the support and fostering of local culture. The main contribution of this research is it offers novel empirical and theoretical insights on the ways in which formalisation and informality are performed. It richly reveals the contested nature of development that is negotiated daily between the individualist developmentality imposed by formalisation and the communitarian- based development possibilities which are enacted through informal trading practices. These developmental possibilities are turned invisible by formalisation as classification enforces a strong reading of street trade which is ontologically distant and even contrary to the community-based values which make street trade not only resilient to formalising efforts but also adaptive to the challenging conditions and, more importantly, central to the cultural and socioeconomic development of these communities

Investigation of protein-metal ion and protein-protein interactions using mass spectrometry and nuclear magnetic spectroscopy

>Magister Scientiae - MScProtein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of a single highly connected interactor can cause widespread disruption of cellular processors including diseases and cancer. Therefore, detailed study of the interactions made by cancer-related proteins will help explain their role in the interaction networks. The investigation of proteins by mass spectrometry (MS) has provided unique opportunities to gain insight into the dynamics of these proteins at the molecular level. MS uses mass analysis for protein characterization, and is currently the most comprehensive and versatile tool in proteomics. MS can provide confirmation of protein samples of interest, accurate molecular mass measurements of proteins, purity of protein samples, detection of posttranslational modifications, and more recently, interactions between two or more proteins. The conventional way of investigating the structure of proteins involves nuclear magnetic resonance (NMR) or X-ray crystallography. Compared to MS these methods are time consuming methods and, furthermore, require a considerable amount of protein. MS has proved to be useful in this regard as it provides insights into the structural arrangement of proteins, and/or their interacting partners, without the need for crystalliastion or the tedious process of backbone assignment before structural and functional annotations can be attributed to the protein of interest. However, in many cases, conventional methods are used parallel to MS to serve as validation of the MS data. The broad objective of this MSc study was to provide structural and functional insights into the function of Retinoblastoma Binding Protein-6 (RBBP6), using a MS approach. The aims were twofold: 1) to investigate metal ion binding by RING (Really Interesting New Gene) finger domains from RBBP6, and 2) to investigate the in vitro interaction between RBBP6 and Hsp 70(Heat Shock Protein 70), and between RBBP6 and Murine Double Minute-2 (Mdm2)

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania