259 research outputs found

    NOESIS: A Framework for Complex Network Data Analysis

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    Network data mining has attracted a lot of attention since a large number of real-world problems have to deal with complex network data. In this paper, we present NOESIS, an open-source framework for network-based data mining. NOESIS features a large number of techniques and methods for the analysis of structural network properties, network visualization, community detection, link scoring, and link prediction. ­e proposed framework has been designed following solid design principles and exploits parallel computing using structured parallel programming. NOESIS also provides a stand-alone graphical user interface allowing the use of advanced software analysis techniques to users without prior programming experience. ­is framework is available under a BSD open-source software license.The NOESIS project was partially supported by the Spanish Ministry of Economy and the European Regional Development Fund (FEDER), under grant TIN2012–36951, and the Spanish Ministry of Education under the program “Ayudas para contratos predoctorales para la formación de doctores 2013” (predoctoral grant BES–2013–064699)

    A Survey On Data Mining Techniques and Applications

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    Data Mining refers to the analysis of experimental data sets to seek out relationships and to summarize the data in ways in which are each comprehensible and helpful. Compared with alternative DM techniques, Intelligent Systems (ISs) based mostly approaches that embody Artificial Neural Networks (ANNs), fuzzy pure mathematics, approximate reasoning, and derivative-free optimisation strategies similar to Genetic Algorithms (GAs), are tolerant of impreciseness, uncertainty, partial truth, and approximation. This paper reviews varieties of Data Mining techniques and applications

    Transportation Research Challenges Based on the Analysis of EU Projects

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    In recent years several projects have been realised in the field of transportation, but there is a lack of systematic analysis of research challenges connected to these projects. Thus, the main aim of this paper is to provide an overview of these challenges through EU funded projects in the field of smart, green and integrated transport. Based on EU strategic documents, reports and roadmaps, 10 topics are identified playing a crucial role in transportation-related research. A systematic analysis of the projects is realised, where the projects collected from an online database in the Horizon 2020 framework programme from 2015 to 2020 are categorised into these topics. The results show that travel behaviour, big data and open data, sustainable mobility planning and smart solutions are covered by several projects which reflect the main research trends. While active and shared modes, multimodal transportation, trip optimisation and Mobility as a Service are also popular topics. Based on the results, the most underrepresented research areas are artificial intelligence and social networks. The analysis of the connections between the research topics could enable the achievement of a long-term paradigm shift in urban mobility, which is beneficial for researchers, professionals and policy makers

    Psychopower and Ordinary Madness: Reticulated Dividuals in Cognitive Capitalism

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    Despite the seemingly neutral vantage of using nature for widely-distributed computational purposes, neither post-biological nor post-humanist teleology simply concludes with the real "end of nature" as entailed in the loss of the specific ontological status embedded in the identifier "natural." As evinced by the ecological crises of the Anthropocene—of which the 2019 Brazil Amazon rainforest fires are only the most recent—our epoch has transfixed the “natural order" and imposed entropic artificial integration, producing living species that become “anoetic,” made to serve as automated exosomatic residues, or digital flecks. I further develop Gilles Deleuze’s description of control societies to upturn Foucauldian biopower, replacing its spacio-temporal bounds with the exographic excesses in psycho-power; culling and further detailing Bernard Stiegler’s framework of transindividuation and hyper-control, I examine how becoming-subject is predictively facilitated within cognitive capitalism and what Alexander Galloway terms “deep digitality.” Despite the loss of material vestiges qua virtualization—which I seek to trace in an historical review of industrialization to postindustrialization—the drive-based and reticulated "internet of things" facilitates a closed loop from within the brain to the outside environment, such that the aperture of thought is mediated and compressed. The human brain, understood through its material constitution, is susceptible to total datafication’s laminated process of “becoming-mnemotechnical,” and, as neuroplasticity is now a valid description for deep-learning and neural nets, we are privy to the rebirth of the once-discounted metaphor of the “cybernetic brain.” Probing algorithmic governmentality while posing noetic dreaming as both technical and pharmacological, I seek to analyze how spirit is blithely confounded with machine-thinking’s gelatinous cognition, as prosthetic organ-adaptation becomes probabilistically molded, networked, and agentially inflected (rather than simply externalized)

    Extracting ontological structures from collaborative tagging systems

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    Socialising around media. Improving the second screen experience through semantic analysis, context awareness and dynamic communities

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    SAM is a social media platform that enhances the experience of watching video content in a conventional living room setting, with a service that lets the viewer use a second screen (such as a smart phone) to interact with content, context and communities related to the main video content. This article describes three key functionalities used in the SAM platform in order to create an advanced interactive and social second screen experience for users: semantic analysis, context awareness and dynamic communities. Both dataset-based and end user evaluations of system functionalities are reported in order to determine the effectiveness and efficiency of the components directly involved and the platform as a whole

    Use of Semantic Technology to Create Curated Data Albums

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    One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discover tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out nonrelevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science

    Digital Innovation and Transformation: a Quasi-Systematic Literature Review

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    Nowadays there are several examples of successful companies that run innovative digital business models. Studies indicate that companies that do not follow the technological tendencies will possibly cease to exist in the next years. Besides, Digital Transformation has a direct impact on relations and forms of consumption. However, although much have been said about this topic, the literature has not established yet a common ground about the meaning of Digital Innovation and Digital Transformation. The purpose of this paper is to identify, analyze and synthesize the various aspects of the main concepts related to Digital Innovation and Transformation (DI&T). We have done a quasi-systematic review of the literature, generating as a primary outcome a list of the main constructs related to DI&T, as well as their definitions. Our main contribution is a map that conceptualizes and relates DI and DT that could be used as a base for future researchers

    The feeble institutional link between the information and communication technologies (ICTs) and poverty in Mexico

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    En las últimas décadas las TIC han sido reconocidas como habilitadoras del desarrollo y reducción de la pobreza. Sin embargo, hay muchos factores que pueden impedir su adopción y apropiación efectiva por parte de los pobres. El objetivo de este trabajo es exponer los efectos que la debilidad institucional del estado mexicano ha tenido en la forma en que se estructura el sector de las telecomunicaciones y, en consecuencia, el débil vínculo entre las TIC y la pobreza en México. Para tal fin, realizamos un análisis documental como parte de una investigación más amplia cuyo objetivo es analizar empíricamente la manera que el Estado mexicano ha impedido a las personas en situación de pobreza el acceso, uso y apropiación de las TIC. Concluímos con algunos de los cambios institucionales que deben realizarse para que las TIC contribuyan de manera más importante a la reducción de la pobreza en México
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