With the rapid increase of Internet of Things-devices(IoT), demand for new machine learning algorithms and modelshas risen. The focus of this project is implementing a federatedlearning (FL) algorithm to detect anomalies in measurementsmade by a water monitoring IoT-sensor. The FL algorithm trainsacross a collection of decentralized IoT-devices, each using thelocal data acquired from the specific sensor. The local machinelearning models are then uploaded to a mutual server andaggregated into a global model. The global model is sent back tothe sensors and is used as a template when training starts againlocally. In this project, we only have had access to one physicalsensor. This has forced us to virtually simulate sensors. Thesimulation was done by splitting the data gathered by the onlyexisting sensor. To deal with the long, sequential data gatheredby the sensor, a long short-term memory (LSTM) network wasused. This is a special type of artificial neural network (ANN)capable of learning long-term dependencies. After analyzing theobtained results it became clear that FL has the potential toproduce good results, provided that more physical sensors aredeployed. / I samband med den snabba ökningen avInternet of Things-enheter (IoT) har efterfrågan på nya algoritmeroch modeller för maskininlärning ökat. Detta projektfokuserar på att implementera en federated learning (FL) algoritmför att detektera avvikelser i mätdata från en sensorsom övervakar vattenkvaliteten. FL algoritmen tränar en samlingdecentraliserade IoT-enheter, var och en med hjälp av lokaldata från sensorn i fråga. De lokala maskininlärningsmodellernaladdas upp till en gemensam server och sammanställs till englobal modell. Den globala modellen skickas sedan tillbaka tillsensorerna och används som mall när den lokala träningen börjarigen. I det här projektet hade vi endast tillgång till en fysisksensor. Vi har därför varit tvungna att simulera sensorer. Dettagjordes genom att dela upp datamängden som samlats in frånden fysiska sensorn. För att hantera den långa sekventiella dataanvänds ett long short-term memory (LSTM) nätverk. Detta ären speciell typ av artificiellt neuronnät (ANN) som är kapabeltatt minnas mönster under en längre tid. Efter att ha analyseratresultaten blev det tydligt att FL har potentialen att produceragoda resultat, givet att fler fysiska sensorer implementeras. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Recent years have witnessed remarkable advancements in machine learning, but with these advances come concerns about data privacy. Machine learning inherently involves learning functions from data, and this process can potentially lead to information leakage through various attacks on the learned model. Additionally, the presence of malicious actors who may poison input data to manipulate the model has become a growing concern. Consequently, the ability to unlearn specific data samples on demand has become critically important. Federated Learning (FL) has emerged as a powerful approach to address these challenges. In FL, multiple participants or clients collaborate to train a single global machine learning model without sharing their training data. However, the issue of machine unlearning is particularly pertinent in FL, especially in scenarios where clients are not fully trustworthy. This paper delves into the investigation of the efficacy of solving machine unlearning problems within the FL framework. The central research question this work tackles is: How can we effectively unlearn the entire dataset from one or multiple clients once an FL training is completed, while maintaining privacy and without access to the data? To address this challenge, we introduce the concept of ”contribution,” which quantifies how much each client contributes to the training of the global FL model. In our implementation, we employ an Encoder-Decoder model on the server’s end to disentangle these contributions as the FL process progresses. Notably, our approach is unique in that there is no existing work that utilizes a similar concept nor similar models. Our findings, supported by extensive experiments on datasets MNIST and FashionMNIST, demonstrate that our proposed approach successfully solves the unlearning task in FL. Remarkably, it achieves results comparable to retraining from scratch without requiring the participation of the specific client whose data needs to be unlearned. Moreover, additional ablation studies indicate the sensitivity of the proposed model to specific structural hyperparameters. / Här har de senaste åren bevittnat enastående framsteg inom maskininlärning, men med dessa framsteg kommer bekymmer om dataskydd. Maskininlärning innebär i grunden att lära sig funktioner från data, och denna process kan potentiellt leda till läckage av information genom olika attacker mot den inlärda modellen. Dessutom har närvaron av illvilliga aktörer som kan förgifta indata för att manipulera modellen blivit en växande oro. Följaktligen har förmågan att avlära specifika datasatser på begäran blivit av avgörande betydelse. Federerad inlärning (FL) har framträtt som en kraftfull metod för att ta itu med dessa utmaningar. I FL samarbetar flera deltagare eller klienter för att träna en enda global maskininlärningsmodell utan att dela sina träningsdata. Emellertid är problemet med maskinavlärande särskilt relevant inom FL, särskilt i situationer där klienterna inte är fullt pålitliga. Denna artikel fördjupar sig i undersökningen av effektiviteten av att lösa problem med maskinavlärande inom FL-ramverket. Den centrala forskningsfråga som detta arbete behandlar är: Hur kan vi effektivt avlära hela datasamlingen från en eller flera klienter när FL-utbildningen är klar, samtidigt som vi bevarar integritet och inte har tillgång till datan? För att ta itu med denna utmaning introducerar vi begreppet ”bidrag,” som kvantifierar hur mycket varje klient bidrar till träningen av den globala FLmodellen. I vår implementering använder vi en Encoder-Decoder-modell på serverns sida för att reda ut dessa bidrag när FL-processen fortskrider. Det är värt att notera att vår metod är unik eftersom det inte finns något befintligt arbete som använder ett liknande koncept eller liknande modeller. Våra resultat, som stöds av omfattande experiment på dataseten MNIST och FashionMNIST, visar att vår föreslagna metod framgångsrikt löser avlärandeuppgiften i FL. Anmärkningsvärt uppnår den resultat som är jämförbara med att träna om från grunden utan att kräva deltagandet av den specifika klient vars data behöver avläras. Dessutom indikerar ytterligare avläggningsstudier känsligheten hos den föreslagna modellen för specifika strukturella hyperparametrar.

<p dir="ltr">The original definition of Nash Equilibrium applied to normal form games, but the notion has now been extended to various other forms of games including leader-follower games (Stackelberg games), extensive form games, stochastic games, games of incomplete information, cooperative games, and so on. We focus on general-sum stochastic Stackelberg games in this work. An example where such games would be natural to consider is in security games where a defender wishes to protect some targets through deployment of limited resources and an attacker wishes to strategically attack the targets to benefit themselves. The hierarchical order of play arises naturally since the defender typically acts first and deploys a strategy, while the attacker observes the strategy ofthe defender before attacking. Another example where this framework fits is in testing during epidemics, where the leader (the government) sets testing policies and the follower (the citizens) decide at every time step whether to get tested. The government wishes to minimize the number of infected people in the population while the follower wishes to minimize the cost of getting sick and testing. This thesis presents a learning algorithm for players to converge to their stationary policies in a general sum stochastic sequential Stackelberg game. The algorithm is a two time scale implicit policy gradient algorithm that provably converges to stationary points of the optimization problems of the two players. Our analysis allows us to move beyond the assumptions of zero-sum or static Stackelberg games made in the existing literature for learning algorithms to converge.</p><p dir="ltr"><br></p>

The objective of this thesis was to investigate how the addition of a privacy-preserving mechanism to a federated learning model was affecting the performance of the model for an image classification task. Further, it was to get knowledge on how the outlook to use federated learning in the biotech industry is and what possible threats and attacks that could obstruct the utilization of federated learning among competitors. In the project four different aggregation algorithms for federated learning were examined. The methods were weighted fedAvg, unweighted FedAvg, weighted FedProx and unweighted FedProx. The experiment was using tensorflow federated to simulate the different methods. They were evaluated using accuracy, loss, recall, precision and F1 score. The result of this study shows that the performance of the deep neural network model is decreasing as differential privacy is introduced to the process. Out of the four aggregation algorithms used, weighted fedProx was the one that performed the best despite the added noise. It was also concluded that federated learning has potential to be used in the biotechnology industry among competitors, but that there are still security threats and attacks to avoid.

<p dir="ltr">Mobile vision is becoming the norm, transforming our daily lives. It powers numerous applications, enabling seamless interactions between the digital and physical worlds, such as augmented reality, real-time object detection, and many others. The popularity of mobile vision has spurred advancements from both computer vision (CV) and mobile edge computing (MEC) communities. The former focuses on improving analytics accuracy through the use of proper deep neural networks (DNNs), while the latter addresses the resource limitations of mobile environments by coordinating tasks between mobile and edge devices, determining which data to transmit and process to enable real-time performance. </p><p dir="ltr"> Despite recent advancements, existing approaches typically integrate the functionalities of the two camps at a basic task level. They rely on a uniform on-device processing scheme that streams the same type of data and uses the same DNN model for identical CV tasks, regardless of the analytical complexity of the current input, input size, or latency requirements. This lack of adaptability to dynamic contexts limits their ability to achieve optimal efficiency in scenarios involving diverse source data, varying computational resources, and differing application requirements. </p><p dir="ltr">Our approach seeks to move beyond task-level adaptation by emphasizing customized optimizations tailored to dynamic use scenarios. This involves three key adaptive strategies: dynamically compressing source data based on contextual information, selecting the appropriate computing model (e.g., DNN or sub-DNN) for the vision task, and establishing a feedback mechanism for context-aware runtime tuning. Additionally, for scenarios involving movable cameras, the feedback mechanism guides the data capture process to further enhance performance. These innovations are explored across three use cases categorized by the capture device: one stationary camera, one moving camera, and cross-camera analytics. </p><p dir="ltr">My dissertation begins with a stationary camera scenario, where we improve efficiency by adapting to the use context on both the device and edge sides. On the device side, we explore a broader compression space and implement adaptive compression based on data context. Specifically, we leverage changes in confidence scores as feedback to guide on-device compression, progressively reducing data volume while preserving the accuracy of visual analytics. On the edge side, instead of training a specialized DNN for each deployment scenario, we adaptively select the best-fit sub-network for the given context. A shallow sub-network is used to “test the waters”, accelerating the search for a deep sub-network that maximizes analytical accuracy while meeting latency requirements.</p><p dir="ltr"> Next, we explore scenarios involving a moving camera, such as those mounted on drones. These introduce new challenges, including increased data encoding demands due to camera movement and degraded analytics performance (e.g., tracking) caused by changing perspectives. To address these issues, we leverage drone-specific domain knowledge to optimize compression for object detection by applying global motion compensation and assigning different resolutions at a tile-granularity level based on the far-near effect. Furthermore, we tackle the more complex task of object tracking and following, where the analytics results directly influence the drone’s navigation. To enable effective target following with minimal processing overhead, we design an adaptive frame rate tracking mechanism that dynamically adjusts based on changing contexts.</p><p dir="ltr"> Last but not least, we extend the work to cross-camera analytics, focusing on coordination between one stationary ground-based camera and one moving aerial camera. The primary challenge lies in addressing significant misalignments (e.g., scale, rotation, and lighting variations) between the two perspectives. To overcome these issues, we propose a multi-exit matching mechanism that prioritizes local feature matching while incorporating global features and additional cues, such as color and location, to refine matches as needed. This approach ensures accurate identification of the same target across viewpoints while minimizing computational overhead by dynamically adapting to the complexity of the matching task. </p><p dir="ltr">While the current work primarily addresses ideal conditions, assuming favorable weather, optimal lighting, and reliable network performance, it establishes a solid foundation for future innovations in adaptive video processing under more challenging conditions. Future efforts will focus on enhancing robustness against adversarial factors, such as sensing data drift and transmission losses. Additionally, we plan to explore multi-camera coordination and multimodal data integration, leveraging the growing potential of large language models to further advance this field.</p>

The main aim of the thesis is to give a complex overview of different types of financial sources, from which new federated states can take benefits, and to give an opinion on the created effectiveness. Additional aims are to sum up the situation of the East German economy after WW2 and also the progress in its reforming during the 90s. Different historical development of the both former divided parts of nowadays Germany is essential because of understanding the economic situation of East Germany in 1990 and the nowadays problems. The first chapter sums up the economic consequences of the post war period, the influence of reparations, demontages and their dimension. In the second chapter follows an evaluation of the main topics of the beginning in the 90s - monetary reform and privatization. The third chapter goes on with the topic of economic reforms in the 90s and defines basic financial programs which are a long-term support to new federated states. Fourth chapter compares main chosen macroeconomic indicators of Germany and EU-27 and then of the old and new federated states. First, economic level of the whole Germany is being analysed and then its regional disparities. The last, fifth, chapter monitors the situation of Germany and its new federated states in the point of structural funds of the European Union.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-04-18T18:05:24Z No. of bitstreams: 1 ANA LÚCIA ROTH_.pdf: 1643482 bytes, checksum: 4e4cda2780cc7255c2502065566263c6 (MD5) / Made available in DSpace on 2016-04-18T18:05:24Z (GMT). No. of bitstreams: 1 ANA LÚCIA ROTH_.pdf: 1643482 bytes, checksum: 4e4cda2780cc7255c2502065566263c6 (MD5) Previous issue date: 2011-08-30 / Nenhuma / O presente trabalho versa sobre a governança de Redes de Cooperação Federadas, uma tipologia específica das Relações Interorganizacionais. O estudo buscou, motivado pelas lacunas teóricas observadas na literatura, identificar os elementos que compõem o sistema de governança das Redes de Cooperação Federadas e como eles podem ser projetados para reduzir os conflitos e os custos de agência nas Federações. Percebeu-se que os estudos que descrevem e analisam os elementos internos da Governança das RIs não chegam a abordar a separação da propriedade e do controle, característico das Redes de Cooperação Federadas. Autores que versam sobre a separação da propriedade e do controle não apresentam os elementos internos da Governança das RIs. Da mesma forma, os estudos não chegam a tratar como os elementos internos da governança (estrutura e mecanismos de governança) podem ser combinados para minimizar os conflitos e custos de agência. Sob a luz da Teoria da Agência, da Teoria da Representação e da Teoria Organizacional usada no contexto das RIs, chegou-se à proposição de três elementos do sistema de governança das Redes de Cooperação Federadas: (a) a estrutura de governança; (b) os mecanismos de governança instituídos para incentivar e controlar o comportamento dos agentes; (c) os mecanismos de governança instituídos para incentivar e controlar o comportamento dos principais. Para a validação empírica do modelo proposto, optou-se pela realização de um estudo qualitativo, de natureza exploratória, por meio do método de estudo de caso múltiplo. O estudo foi operacionalizado por meio de dois estudos de caso: um na Rede Âncora Brasil e o outro na Rede Construir. Os resultados permitem afirmar que, embora presentes, os elementos estruturais e mecanismos de governança sobre os principais e sobre os agentes apresentam características distintas. Há, em um extremo, uma Federação com um maior nível de instâncias de decisão, maior número de atividades desenvolvidas pela Federação, o que tende a levar a uma maior centralização, formalização, padronização, coordenação e controle. No outro extremo, encontra-se uma Federação com poucas instâncias de decisão, menor número de atividades desenvolvidas pela Federação, o que tende a levar a uma descentralização, menor formalização, padronização, coordenação e controle. O estudo empírico levou à adição do elemento representação e participação na estrutura de governança das Redes de Cooperação Federadas. Os mecanismos internos e externos de governança, amplamente utilizados nas corporações também foram identificados no contexto das Redes de Cooperação Federadas. Constatou-se, entretanto, que o Conselho de Administração ou órgão correspondente é o mecanismo mais efetivo para redução dos custos e conflitos de agência. Entre as contribuições teóricas do trabalho, destaca-se a adoção de uma nova perspectiva do conceito de governança das Redes de Cooperação Federadas sob a luz da Teoria da Agência. / This study concerns Federated Cooperative Networks governance, a specific Interorganizational Relationship (IOR) typology. Motivated by a theoretical gap in this subject, we sought to identify the elements forming the Federated Cooperative Networks governance system and how they can be designed to reduce conflicts and agency costs in Federations. It was noticed that studies describing and analyzing internal IORs governance elements do not approach separation of ownership from control, characteristic of Federated Cooperative Networks. Authors who discuss separation of ownership from control don’t show the internal elements of IOR governance. And the studies don’t discuss how the internal governance elements (governance structure and mechanisms) might be combined to minimize conflicts and agency costs either. Based on the Agency Theory, Representation Theory and Organizational Theory employed in IORs context, we have proposed three elements for the Federated Cooperative Networks governance system: (a) a governance structure; (b) governance mechanisms instituted to encourage and control the behavior of agents; (c) governance mechanisms instituted to encourage and control the behavior of principals. For the empirical validation of these elements, we have chosen to perform a qualitative study, of exploratory nature, through the multiple case study method. The study was operated through two case studies: one at Rede Âncora Brasil and the other at Rede Construir. The results allow us to assert that, although present, structural elements and governance mechanisms over principals and agents show distinct features. On one extreme, there is a Federation with a higher level of decision instances, a higher number of activities developed by the Federation, which tend to lead to more centralization, formalization, standardization, coordination and control. On the other extreme, a Federation with little decision instances, and a lower number of activities developed by the Federation, which tend to lead to decentralization, less formalization, standardization, coordination and control. The empirical study added the element representation and participation in the Federated Cooperative Networks governance structure. The internal and external governance mechanisms, widely employed in corporations, were also identified in the Federated Cooperative Networks context. However, we have found that the Administrative Council, or corresponding agency, is the most effective mechanism in reducing agency costs and conflicts. Among the theoretical contributions of the study, adopting a new perspective in the concept of Federated Cooperative Networks governance under the light of the Agency theory can be stressed.

Os atuais recursos tecnológicos têm favorecido o desenvolvimento de diferentes métodos de disseminação seletiva de informações, permitindo, inclusive, maior autonomia aos usuários. Neste contexto, teve-se como objetivo analisar o processo de disseminação seletiva de informações, por meio de estudo exploratório em uma biblioteca digital federada, visando a valorizar a mediação por intervenção humana. Para tanto, realizou-se uma revisão bibliográfica sobre os temas disseminação seletiva de informações e bibliotecas digitais federadas, assumindo-se a visão de mediação, a partir da perspectiva de Kuhlthau. Realizou-se, ainda, um estudo de caso no NEP (New Economics Papers), um serviço da biblioteca digital RePEc (Research Papers in Economics), sendo a coleta de dados realizada a partir de variadas fontes de evidências. Em relação ao questionário usado na coleta de dados, dos 61 editores temáticos voluntários, que faziam a seleção de informações a serem disseminadas nas categorias temáticas do NEP, contou-se com 41 respondentes. Para a análise dos dados, derivados das respostas do questionário, utilizou-se análise de conteúdo, buscando a identificação de fatores relevantes relacionados às variáveis analisadas (interação entre mediadores e usuários, seleção dos documentos, motivação dos mediadores, impacto do serviço e perfil dos mediadores), promovendo, quando necessário, o agrupamento de respostas semelhantes em categorias, enfatizando a ocorrência de determinado fator e não sua freqüência. Dentre os resultados destacam-se: caracterização de três distintas gerações de serviços de disseminação seletiva de informações, em relação ao desenvolvimento tecnológico; identificação de distintas possibilidades e níveis de mediação nos serviços de disseminação seletiva de informações; identificação de fatores correspondentes às variáveis analisadas em relação à mediação realizada por meio de intervenção humana, em serviços de disseminação seletiva de informações em bibliotecas digitais federadas. Conclui-se que, embora a tecnologia possibilite a autonomia por parte do usuário, em relação aos serviços de disseminação seletiva de informações, é viável um planejamento prévio que reconheça a possibilidade de se atuar em diferentes níveis de mediação a serem adotados, uma vez que a presença da mediação pode agregar valor ao serviço. / Technological advances has facilitated the development of various resources enabling the implementation of selective dissemination of information services which offer autonomy to users. Thus, the objective was to analyze the process of selective dissemination of information, through an exploratory study in a federated digital library, aiming to enhance the mediation by human intervention. For this, a literature review was made comprising the themes: selective dissemination of information and digital libraries, assuming mediation from the perspective of Kuhlthau. Also, it was conducted a case study based on NEP (New Economics Papers), a service of the digital library RePEc (Research Papers in Economics) being the data collection made from various sources of evidence. Regarding the questionnaire used in the data collection, out of 61 volunteers, who were responsible for selecting information on the NEP themes to be disseminated, 41 responded the questionnaire. For data analysis, derived from responses from the questionnaires, it was used content analysis, seeking to identify relevant factors related to the analyzed variables (interaction between mediators and users, documents\' selection, mediators\' motivation, services impact and mediators\' profile), promoting, when necessary, the grouping of similar responses into categories, emphasizing thus, the occurrence of a particular factor and not it\'s frequency. Among the results are: characterization of three different generations of selective dissemination of information services, in relation to technological development; identification of different possibilities and levels of mediation in services of selective dissemination of information; identification of factors related to the variables analyzed, in relation to the mediation made by means of human intervention in services of selective dissemination of information. It is found that, although the technology allows the autonomy of the user, referring to the selective dissemination of information services, it is possible to make a previous planning that recognize the possibility of acting from different levels of mediation to be adopted, since the presence of mediation can add value to the service.

Os atuais recursos tecnológicos têm favorecido o desenvolvimento de diferentes métodos de disseminação seletiva de informações, permitindo, inclusive, maior autonomia aos usuários. Neste contexto, teve-se como objetivo analisar o processo de disseminação seletiva de informações, por meio de estudo exploratório em uma biblioteca digital federada, visando a valorizar a mediação por intervenção humana. Para tanto, realizou-se uma revisão bibliográfica sobre os temas disseminação seletiva de informações e bibliotecas digitais federadas, assumindo-se a visão de mediação, a partir da perspectiva de Kuhlthau. Realizou-se, ainda, um estudo de caso no NEP (New Economics Papers), um serviço da biblioteca digital RePEc (Research Papers in Economics), sendo a coleta de dados realizada a partir de variadas fontes de evidências. Em relação ao questionário usado na coleta de dados, dos 61 editores temáticos voluntários, que faziam a seleção de informações a serem disseminadas nas categorias temáticas do NEP, contou-se com 41 respondentes. Para a análise dos dados, derivados das respostas do questionário, utilizou-se análise de conteúdo, buscando a identificação de fatores relevantes relacionados às variáveis analisadas (interação entre mediadores e usuários, seleção dos documentos, motivação dos mediadores, impacto do serviço e perfil dos mediadores), promovendo, quando necessário, o agrupamento de respostas semelhantes em categorias, enfatizando a ocorrência de determinado fator e não sua freqüência. Dentre os resultados destacam-se: caracterização de três distintas gerações de serviços de disseminação seletiva de informações, em relação ao desenvolvimento tecnológico; identificação de distintas possibilidades e níveis de mediação nos serviços de disseminação seletiva de informações; identificação de fatores correspondentes às variáveis analisadas em relação à mediação realizada por meio de intervenção humana, em serviços de disseminação seletiva de informações em bibliotecas digitais federadas. Conclui-se que, embora a tecnologia possibilite a autonomia por parte do usuário, em relação aos serviços de disseminação seletiva de informações, é viável um planejamento prévio que reconheça a possibilidade de se atuar em diferentes níveis de mediação a serem adotados, uma vez que a presença da mediação pode agregar valor ao serviço. / Technological advances has facilitated the development of various resources enabling the implementation of selective dissemination of information services which offer autonomy to users. Thus, the objective was to analyze the process of selective dissemination of information, through an exploratory study in a federated digital library, aiming to enhance the mediation by human intervention. For this, a literature review was made comprising the themes: selective dissemination of information and digital libraries, assuming mediation from the perspective of Kuhlthau. Also, it was conducted a case study based on NEP (New Economics Papers), a service of the digital library RePEc (Research Papers in Economics) being the data collection made from various sources of evidence. Regarding the questionnaire used in the data collection, out of 61 volunteers, who were responsible for selecting information on the NEP themes to be disseminated, 41 responded the questionnaire. For data analysis, derived from responses from the questionnaires, it was used content analysis, seeking to identify relevant factors related to the analyzed variables (interaction between mediators and users, documents\' selection, mediators\' motivation, services impact and mediators\' profile), promoting, when necessary, the grouping of similar responses into categories, emphasizing thus, the occurrence of a particular factor and not it\'s frequency. Among the results are: characterization of three different generations of selective dissemination of information services, in relation to technological development; identification of different possibilities and levels of mediation in services of selective dissemination of information; identification of factors related to the variables analyzed, in relation to the mediation made by means of human intervention in services of selective dissemination of information. It is found that, although the technology allows the autonomy of the user, referring to the selective dissemination of information services, it is possible to make a previous planning that recognize the possibility of acting from different levels of mediation to be adopted, since the presence of mediation can add value to the service.

Product information search has become one of the most important application areas of the Web. Especially considering pricey technical products, consumers tend to carry out intensive research activities previous to the actual acquisition for creating an all-embracing view on the product of interest. Federated search backed by ontology-based product information representation shows great promise for easing this research process. The topic of this thesis is to develop a comprehensive technique for locating, extracting, and integrating information of arbitrary technical products in a widely unsupervised manner. The resulting homogeneous information sets allow a potential consumer to effectively compare technical products based on an appropriate federated product information system. / Die Produktinformationssuche hat sich zu einem der bedeutendsten Themen im Web entwickelt. Speziell im Bereich kostenintensiver technischer Produkte führen potenzielle Konsumenten vor dem eigentlichen Kauf des Produkts langwierige Recherchen durch um einen umfassenden Überblick für das Produkt von Interesse zu erlangen. Die föderierte Suche in Kombination mit ontologiebasierter Produktinformationsrepräsentation stellt eine mögliche Lösung dieser Problemstellung dar. Diese Dissertation stellt Techniken vor, die das automatische Lokalisieren, Extrahieren und Integrieren von Informationen für beliebige technische Produkte ermöglichen. Die resultierenden homogenen Produktinformationen erlauben einem potenziellen Konsumenten, zugehörige Produkte effektiv über ein föderiertes Produktinformationssystem zu vergleichen.