Relevant bibliographies by topics / Aggregation Platform

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Aggregation Platform'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Aggregation Platform"

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Bray, Natasha. "A platform for probing protein-aggregation inhibitors." Nature Reviews Drug Discovery 15, no. 2 (January 29, 2016): 85. http://dx.doi.org/10.1038/nrd.2016.8.

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Dai, Zhihuang, and Michael J. Scott. "Effective Product Family Design Using Preference Aggregation." Journal of Mechanical Design 128, no. 4 (October 11, 2005): 659–67. http://dx.doi.org/10.1115/1.2197835.

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The development of product families, groups of products that share a common platform, is one way to provide product variety while keeping design and production costs low. The design of a product platform can be formulated as a multicriteria optimization problem in which the performances of individual products trade off against each other and against the objective of platform standardization. The problem is often solved in two stages: one to determine the values of the shared platform variables and a second to optimize the product family members with respect to specific targets. In the first stage, it is common to target the mean and variability of performance when fixing the values of platform variables. This paper contributes three new methods for platform development. The new methods are demonstrated on an electric motor example from the platform design literature, and the results are compared to those from existing methods. First, a preference aggregation method is applied to aggregate the multiple objectives into a single overall objective function. On the example problem, this approach gives superior results to existing techniques. Second, an alternative method that targets the minimum and maximum of the range of performance across the platform, instead of the mean and standard deviation, is proposed and shown to succeed where the existing method may fail. Third, a single-stage optimization approach which solves for both platform and nonplatform variables in a single pass is presented. This method delivers notably superior performance on the example problem but will, in general, incur greater computational expense.
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Cunha, David, Pedro Neves, and Pedro Sousa. "PaaS manager: A platform-as-a-service aggregation framework." Computer Science and Information Systems 11, no. 4 (2014): 1209–28. http://dx.doi.org/10.2298/csis130828028c.

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The advent of Cloud Computing opened new opportunities in several areas, namely in the application development processes. As consequence, nowadays, PaaS (Platform-as-a-Service) service model allows simpler and flexible deployment strategies of applications, avoiding the need for dedicated networks, servers, storage, and other services. Within this context, several PaaS providers exist in the market, but each one having specific characteristics, proprietary technologies and Application Programming Interfaces (APIs). Based on such assumptions, this work addresses the challenge of devising a PaaS aggregation solution with the objective of unifying the information and management processes of applications created in PaaS environments. The proposed solution, denominated as PaaS Manager, take the form of a PaaS API aggregator aiming to struggle the existing lock-in in the PaaS market. In this perspective, this paper describes the specification, development and test of the proposed PaaS Manager solution. As result of this framework, end-users are able to select the most appropriate PaaS platform for an application, interacting with any supported vendor through a unique deployment and management interface.
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Wang, Fang Fang, Xiu Yuan Zhang, and Gang Wang. "Study on Urban Rail Transit Platform Aggregation Passenger." Applied Mechanics and Materials 253-255 (December 2012): 1812–15. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1812.

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It is the basis for increasing attraction of rail transit and maximizing the attraction of public transport to focus on summarizing the pattern and experience of growing rail passenger flow, and studying the characteristics of trip assignment. This paper studied specifically on the passenger assembling of the urban rail transit platform, and designed the calculation methods about assembling passengers on platform through the analysis of passenger flow characteristics. Based on the specific situation of the subway of Beijing south station, this paper analyzed the assembling of platform and obtained assembling data under different conditions. The result shows that, in order to smooth the assembling of platform, we could reduce the train arrival time-gap, stagger the up and down train’s arrival time and increase their arrival time-gap in a proper way.
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YU, Hui. "PCP: P2P-based computing resource sharing and aggregation platform." Journal of Computer Applications 29, no. 10 (December 17, 2009): 2647–51. http://dx.doi.org/10.3724/sp.j.1087.2009.02647.

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Xu, Youwei, Shengqun Tang, Yan Yang, Yang Xu, and Ling Li. "Development and research on the internet resources aggregation platform." Wuhan University Journal of Natural Sciences 12, no. 2 (March 2007): 243–48. http://dx.doi.org/10.1007/s11859-006-0029-x.

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KAO, BEN, and RON KATRIEL. "SUBSAMPLED MODEL AGGREGATION." International Journal on Artificial Intelligence Tools 14, no. 03 (June 2005): 385–97. http://dx.doi.org/10.1142/s0218213005002168.

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There has been a recent push for a new framework of learning, due in part to the availability of storage, networking and the abundance of very large datasets. This framework argues for parallelized learning algorithms that can operate on a distributed platform and have the ability to terminate early in the likely event that data size is too inundating. Methods described herein propose a subsampled model aggregation technique based on the bagging algorithm. It is capable of significant run-time reduction with no loss in modeling performance. These claims were validated with a variety of base-learning algorithms on large web and newswire datasets.
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Tarabichi, Yasir, Adam Frees, Steven Honeywell, Courtney Huang, Andrew M. Naidech, Jason H. Moore, and David C. Kaelber. "The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform." ACI Open 05, no. 01 (January 2021): e36-e46. http://dx.doi.org/10.1055/s-0041-1731004.

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Abstract Objective Learning healthcare systems use routinely collected data to generate new evidence that informs future practice. While implementing an electronic health record (EHR) system can facilitate this goal for individual institutions, meaningfully aggregating data from multiple institutions can be more empowering. Cosmos is a cross-institution, single EHR vendor-facilitated data aggregation tool. This work aims to describe the initiative and illustrate its potential utility through several use cases. Methods Cosmos is designed to scale rapidly by leveraging preexisting agreements, clinical health information exchange networks, and data standards. Data are stored centrally as a limited dataset, but the customer facing query tool limits results to prevent patient reidentification. Results In 2 years, Cosmos grew to contain EHR data of more than 60 million patients. We present practical examples illustrating how Cosmos could further efforts in chronic disease surveillance (asthma and obesity), syndromic surveillance (seasonal influenza and the 2019 novel coronavirus), immunization adherence and adverse event reporting (human papilloma virus and measles, mumps, rubella, and varicella vaccination), and health services research (antibiotic usage for upper respiratory infection). Discussion A low barrier of entry for Cosmos allows for the rapid accumulation of multi-institutional and mostly de-duplicated EHR data to power research and quality improvement queries characteristic of learning healthcare systems. Limitations are being vendor-specific, an “all or none” contribution model, and the lack of control over queries run on an institution's healthcare data. Conclusion Cosmos provides a model for within-vendor data standardization and aggregation and a steppingstone for broader intervendor interoperability.
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Fomba, Soumana, Pascale Zarate, Marc Kilgour, Guy Camilleri, Jacqueline Konate, and Fana Tangara. "A Recommender System Based on Multi-Criteria Aggregation." International Journal of Decision Support System Technology 9, no. 4 (October 2017): 1–15. http://dx.doi.org/10.4018/ijdsst.2017100101.

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Recommender systems aim to support decision-makers by providing decision advice. We review briefly tools of Multi-Criteria Decision Analysis (MCDA), including aggregation operators, that could be the basis for a recommender system. Then we develop a multi-criteria recommender system, STROMa (SysTem of RecOmmendation Multi-criteria), to support decisions by aggregating measures of performance contained in a performance matrix. The system makes inferences about preferences using a partial order on criteria input by the decision-maker. To determine a total ordering of the alternatives, STROMa uses a multi-criteria aggregation operator, the Choquet integral of a fuzzy measure. Thus, recommendations are calculated using partial preferences provided by the decision maker and updated by the system. An integrated web platform is under development.
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Jariwala, Vivaksha, Himanshu Patel, Parth Patel, and Devesh C. Jinwala. "Integrity and Privacy Preserving Secure Data Aggregation in Wireless Sensor Networks." International Journal of Distributed Systems and Technologies 5, no. 3 (July 2014): 77–99. http://dx.doi.org/10.4018/ijdst.2014070104.

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Data aggregation based on in-network processing is useful in improving the communications overhead in Wireless Sensor Networks (WSNs) by reducing the overall number of packets communicated to the base station. However, due to the fusion of data items sourced at different nodes into a single one, the security of the aggregated data as well as that of the aggregating node, demands critical investigation. This paper observes that though there have been substantial numbers of research attempts recently in proposing techniques for secure data aggregation, there is still a need for a coherent, integrated framework for secure data aggregation. It proposes such an integrated framework for secure data aggregation in this paper. The proposed framework implements a secure data aggregation protocol, offering the attributes viz. confidentiality, privacy, authentication, robustness, as well as data integrity using a defined data aggregation topology. In addition to that, the proposed framework is based on a zero configuration protocol that supports a generation of a defined aggregation topology and a key exchange procedure. This work supports the framework with detailed security analysis and performance evaluation on TinyOS platform using TOSSIM as the base simulator. Through humble observations, this is an unique attempt that integrates the support for security features, topology generation and key management in a single, secure data aggregation protocol; substantiating the proposal with elaborate experimental evaluation, too.
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Dissertations / Theses on the topic "Aggregation Platform"

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Ström, Erik. "Podcast aggregation system : with cross platform synchronization." Thesis, Mittuniversitetet, Avdelningen för data- och systemvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-33281.

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The prime objective of this study was to research the possibilities of synchronizing information such as episodic progression and tracking as well as subscriptions in regards to audio podcasting channels , and to do this without the need of consideration to the underlying platforms. An application providing podcatching capabilities is developed and its features determined through the process of comparing similar existing solutions. Based on this comparison a model is shaped and used as a tool of measuring podcatching capabilities of any media playing software, including the very solution resulting from this study. Supporting questions such as how to find and subscribe to podcast channels will be answered through the analysis of syndication feeds , their structure and how its contents may not only be read but also stored to best accomodate requirements deemed as necessary.
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Yan, Jing. "Analysis of amyloid aggregation on water-based microfluidics platform." Thesis, University of Cambridge, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708312.

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Saunders, Janet Catherine. "An in vivo platform for identifying protein aggregation inhibitors." Thesis, University of Leeds, 2014. http://etheses.whiterose.ac.uk/7622/.

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Protein aggregation is the basis of a vast array of diseases and one of the most expensive problems to overcome during production of biopharmaceuticals. The tendency of proteins to aggregate ensures that demanding purification techniques are a pre-requisite to in vitro analysis of aggregation mechanisms and screening for aggregation inhibitors. In this thesis, a powerful new system was developed to identify aggregation-prone sequences in vivo, and to screen for inhibitors of aggregation. The screen is based on a β-lactamase-tripartite fusion system, where the minimal inhibitory concentration of antibiotic, conferred by the β-lactamase enzyme, is used to evaluate the level of test protein aggregation. Using this in vivo system, the aggregation propensity of the two disease-related proteins human islet amyloid polypeptide (hIAPP) and amyloid beta peptide (Aβ) was found to be significantly higher than non-aggregating controls. Importantly, this system provides a new approach to assess aggregation-propensity without the need for purified protein. The system was used to screen small molecules for their aggregation-inhibiting properties against hIAPP. It was found that many results correlated well with the published literature on these molecules, but notably, a number did not. In vitro analysis of hIAPP aggregation in the presence of these molecules validated the results from the in vivo assay, refuting a number of published studies and confirming the power of the tripartite system for identifying aggregation inhibitors. Finally, the system was used to differentiate between an aggregating and non-aggregating human VH antibody domain, to demonstrate the application of the screen to biopharmaceuticals. The in vivo system successfully identified the aggregating test protein, wherein the addition of excipients prevented its aggregation in vivo in a titratable manner. Overall the work presented herein describes a novel, and experimentally simple, in vivo system that provides rapid and accurate analysis of protein aggregation and its inhibition.
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Olurin, Olumuyiwa. "Policy Merger System for P3P in a Cloud Aggregation Platform." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/23624.

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The need for aggregating privacy policies is present in a variety of application areas today. In traditional client/server models, websites host services along with their policies in different private domains. However, in a cloud-computing platform where aggregators can merge multiple services, users often face complex decisions in terms of choosing the right services from service providers. In this computing paradigm, the ability to aggregate policies as well as services will be useful and more effective for users that are privacy conscious regarding their sensitive or personal information. This thesis studies the problems associated with the Platform for Privacy Preference (P3P) language, and the present issues with communicating and understanding the P3P language. Furthermore, it discusses some efficient strategies and algorithms for the matching and the merging processes, and then elaborates on some privacy policy conflicts that may occur after merging policies. Lastly, the thesis presents a tool for matching and merging P3P policies. If successful, the merge produces an aggregate policy that is consistent with the policies of all participating service providers.
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Janoška, Daniel. "Moderní technologie v OLAP." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235902.

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OLAP systems are sought-after tool which are deployed in companies and industry environment. The fundamental task of these systems are support of executive management. This work is dealing with OLAP analysis and its capabilities. It also discussed FLEX and AIR technology, their base principles and functions.
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Schwedhelm, Ivo Peter [Verfasser], Jan [Gutachter] Hansmann, Philipp [Gutachter] Wiedemann, and Heike [Gutachter] Walles. "A non-invasive microscopy platform for the online monitoring of hiPSC aggregation in suspension cultures in small-scale stirred tank bioreactors / Ivo Peter Schwedhelm ; Gutachter: Jan Hansmann, Philipp Wiedemann, Heike Walles." Würzburg : Universität Würzburg, 2019. http://d-nb.info/1202013600/34.

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Ivanou, Aliaksandr. "A Centralised data aggregation layer across different consuming platforms." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-263260.

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The master thesis represents the solution for data aggregation between different consuming platforms. The work is divided on two parts. The first part shows how to improve the data aggregation using Content Delivery networks, while the second part introduces the SQL-like language for efficiently gathering data between different servers.
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Domingos, João Nuno Silva Tabar. "On the cloud deployment of a session abstraction for service/data aggregation." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/9923.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
The global cyber-infrastructure comprehends a growing number of resources, spanning over several abstraction layers. These resources, which can include wireless sensor devices or mobile networks, share common requirements such as richer inter-connection capabilities and increasing data consumption demands. Additionally, the service model is now widely spread, supporting the development and execution of distributed applications. In this context, new challenges are emerging around the “big data” topic. These challenges include service access optimizations, such as data-access context sharing, more efficient data filtering/ aggregation mechanisms, and adaptable service access models that can respond to context changes. The service access characteristics can be aggregated to capture specific interaction models. Moreover, ubiquitous service access is a growing requirement, particularly regarding mobile clients such as tablets and smartphones. The Session concept aggregates the service access characteristics, creating specific interaction models, which can then be re-used in similar contexts. Existing Session abstraction implementations also allow dynamic reconfigurations of these interaction models, so that the model can adapt to context changes, based on service, client or underlying communication medium variables. Cloud computing on the other hand, provides ubiquitous access, along with large data persistence and processing services. This thesis proposes a Session abstraction implementation, deployed on a Cloud platform, in the form of a middleware. This middleware captures rich/dynamic interaction models between users with similar interests, and provides a generic mechanism for interacting with datasources based on multiple protocols. Such an abstraction contextualizes service/users interactions, can be reused by other users in similar contexts. This Session implementation also permits data persistence by saving all data in transit in a Cloud-based repository, The aforementioned middleware delivers richer datasource-access interaction models, dynamic reconfigurations, and allows the integration of heterogenous datasources. The solution also provides ubiquitous access, allowing client connections from standard Web browsers or Android based mobile devices.
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Du, Qianzhou. "Extracting the Wisdom of Crowds From Crowdsourcing Platforms." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/102032.

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Enabled by the wave of online crowdsourcing activities, extracting the Wisdom of Crowds (WoC) has become an emerging research area, one that is used to aggregate judgments, opinions, or predictions from a large group of individuals for improved decision making. However, existing literature mostly focuses on eliciting the wisdom of crowds in an offline context—without tapping into the vast amount of data available on online crowdsourcing platforms. To extract WoC from participants on online platforms, there exist at least three challenges, including social influence, suboptimal aggregation strategies, and data sparsity. This dissertation aims to answer the research question of how to effectively extract WoC from crowdsourcing platforms for the purpose of making better decisions. In the first study, I designed a new opinions aggregation method, Social Crowd IQ (SCIQ), using a time-based decay function to eliminate the impact of social influence on crowd performance. In the second study, I proposed a statistical learning method, CrowdBoosting, instead of a heuristic-based method, to improve the quality of crowd wisdom. In the third study, I designed a new method, Collective Persuasibility, to solve the challenge of data sparsity in a crowdfunding platform by inferring the backers' preferences and persuasibility. My work shows that people can obtain business benefits from crowd wisdom, and it provides several effective methods to extract wisdom from online crowdsourcing platforms, such as StockTwits, Good Judgment Open, and Kickstarter.
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Andersson, Oskar. "Design of a system for visualizing trends and behaviors based on customer data." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175633.

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Big amounts of data are produced every day in companies. By analyzing and visualizing the data a lot of insights can be gained. The company Solution Xperts wanted to create a system that could import and visualize Big Data. In this work a system was created and evaluated. The report shows that it can be difficult to visualize Big Data, but when a system is created it can easily be adapted to data coming from different companies and provide a lot of value to companies and organizations.
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Book chapters on the topic "Aggregation Platform"

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Ben-Ameur, Houssein, François Bédard, Stéphane Vaucher, Peter Kropf, Brahim Chaib-draa, and Robert Gérin-Lajoie. "NADIM-Travel: A Multiagent Platform for Travel Services Aggregation." In Information and Communication Technologies in Tourism 2004, 293–304. Vienna: Springer Vienna, 2004. http://dx.doi.org/10.1007/978-3-7091-0594-8_28.

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Duennwald, Martin L. "Yeast as a Platform to Explore Polyglutamine Toxicity and Aggregation." In Methods in Molecular Biology, 153–61. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-438-8_11.

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Mazurek, Cezary, Marcin Mielnicki, Aleksandra Nowak, Maciej Stroiński, Marcin Werla, and Jan Węglarz. "Architecture for Aggregation, Processing and Provisioning of Data from Heterogeneous Scientific Information Services." In Intelligent Tools for Building a Scientific Information Platform, 529–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35647-6_32.

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Aguilar, Juan, and Alicia Arce. "Analysis of Data Generated by an Automated Platform for Aggregation of Distributed Energy Resources." In Communications in Computer and Information Science, 282–94. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41913-4_23.

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Yan, Xuzhou, Mingming Zhang, and Feihe Huang. "Aggregation-Induced Emission on Supramolecular Coordination Complexes Platforms." In Principles and Applications of Aggregation-Induced Emission, 163–94. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99037-8_7.

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Cunha, David, Pedro Neves, and Pedro Sousa. "A Platform-as-a-Service API Aggregator." In Advances in Intelligent Systems and Computing, 807–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36981-0_75.

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Griffin, Keith, Maciej Dabrowski, and John Breslin. "Real-Time Data Aggregation in Distributed Enterprise Social Platforms." In IFIP Advances in Information and Communication Technology, 711–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40543-3_74.

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Papadokostaki, Koralia, Stavros Charitakis, George Vavoulas, Stella Panou, Paraskevi Piperaki, Aris Papakonstantinou, Savvas Lemonakis, et al. "News Articles Platform: Semantic Tools and Services for Aggregating and Exploring News Articles." In Strategic Innovative Marketing, 511–19. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56288-9_68.

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Gharahighehi, Alireza, Celine Vens, and Konstantinos Pliakos. "Multi-stakeholder News Recommendation Using Hypergraph Learning." In ECML PKDD 2020 Workshops, 531–35. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65965-3_36.

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AbstractRecommender systems are meant to fulfil user preferences. Nevertheless, there are multiple examples where users are not the only stakeholder in a recommendation platform. For instance, in news aggregator websites apart from readers, one can consider magazines (news agencies) or authors as other stakeholders. A multi-stakeholder recommender system generates a ranked list of items taking into account the preferences of multiple stakeholders. In this study, news recommendation is handled as a hypergraph ranking task, where relations between multiple types of objects and stakeholders are modeled in a unified hypergraph. The obtained results indicate that ranking on hypergraphs can be utilized as a natural multi-stakeholder recommender system that is able to adapt recommendations based on the importance of stakeholders.
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Tsotsolas, Nikos, Faidon Komisopoulos, Philip Papadopoulos, and Eleni Koutsouraki. "An Integrated LoRa-Based IoT Platform Serving Smart Farming and Agro-Logistics." In Emerging Ecosystem-Centric Business Models for Sustainable Value Creation, 132–58. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-4843-1.ch006.

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The value chain of agri-food is radically changed due the fact that consumers, as well as various players in the agro-logistics chain, seek for increased and trustful food safety. Given the specific characteristics of the agri-food supply chain, having numerous origin points, several aggregations hubs at different levels and then again numerous points of sales, the need of a holistic approach in collecting, forwarding and interpreting data in an interoperable way is a dire need. In this chapter, the authors present the architecture of the traceability platform KalaΘosTM and its IoT management module called, GP CoreIoTTM. The KalaΘos infrastructure includes a network of sensors devices at farms, equipment, trucks, aggregation, processing, and logistics facilities, connected to a network of LoRa gateways. Its open architecture focuses on semantic and syntactic interoperability approaches for joint exploitation of data collected and managed by other systems with similar aims and scope.
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Conference papers on the topic "Aggregation Platform"

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Maheshwari, Piyush, Shalini Kapoor, Krishna Kummamuru, and Gopal Pingali. "ICT Enabled Smart Rural Aggregation Platform." In 2011 Annual SRII Global Conference (SRII). IEEE, 2011. http://dx.doi.org/10.1109/srii.2011.66.

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Wang, Lei, and Zhide Chen. "Optimal aggregation platform mechanism for mobile App auction." In 2014 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2014. http://dx.doi.org/10.1109/icalip.2014.7009860.

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Mawane, Jamal, Abdelwahab Naji, and Mohamed Ramdani. "Recommender E-Learning platform using sentiment analysis aggregation." In SITA'20: Theories and Applications. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3419604.3419784.

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Hanglong Zhan, Lianghuan Kang, Lantao Liu, and Donggang Cao. "Scalable Resource Aggregation Service of an ErlangOTP PaaS Platform." In 2013 IEEE 7th International Symposium on Service Oriented System Engineering (SOSE 2013). IEEE, 2013. http://dx.doi.org/10.1109/sose.2013.76.

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Liu, Jianxiao, Da Ning, Kai Xing, Zonglin Tian, Panbiao Liu, and Feng Liu. "Web Service Aggregation Platform Implementation Based on Join Operation." In 2015 International Conference on Advances in Mechanical Engineering and Industrial Informatics. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/ameii-15.2015.208.

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Gomes, I. L. R., R. Laia, H. M. I. Pousinho, R. Melicio, and V. M. F. Mendes. "Aggregation Platform for Wind-PV-Thermal Technology in Electricity Market." In 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM). IEEE, 2018. http://dx.doi.org/10.1109/speedam.2018.8445348.

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Troglio, Giulia, Stefano Bianchi, and Gianni Viano. "LIBRA: A cloud-based platform for production and load aggregation." In 2019 1st International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED). IEEE, 2019. http://dx.doi.org/10.1109/synergy-med.2019.8764106.

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Di Ferdinando, Antonio, Ricardo Lent, Erol Gelenbe, Alberto Rosi, and Franco Zambonelli. "A platform for pervasive combinatorial trading with opportunistic self-aggregation." In 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM). IEEE, 2008. http://dx.doi.org/10.1109/wowmom.2008.4594897.

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Diaz, Isael, Rodolfo Torrea-Duran, Sofie Pollin, Liesbet Van der Perre, and Viktor Owall. "Selective channelization on an SDR platform for LTE-a carrier aggregation." In 2012 19th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2012). IEEE, 2012. http://dx.doi.org/10.1109/icecs.2012.6463738.

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Mihaela, Coroiu, Chindris Mircea, and Dumitrascu Daniel. "Smart Hub Electric Energy Data Aggregation Platform for Prosumers Grid Integration." In 2021 9th International Conference on Modern Power Systems (MPS). IEEE, 2021. http://dx.doi.org/10.1109/mps52805.2021.9492713.

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Reports on the topic "Aggregation Platform"

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Chiou, Lesley, and Catherine Tucker. Content Aggregation by Platforms: The Case of the News Media. Cambridge, MA: National Bureau of Economic Research, July 2015. http://dx.doi.org/10.3386/w21404.

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