Uit de aankondiging: "Steeds meer systemen loggen gegevens over hoe het bedrijfsproces verloopt, maar loopt het proces wel zoals het bedoeld was? Wat zijn de knelpunten? Text mining is vaak lastig doordat er tijdstippen ontbreken, process mining kan niet werken zonder tijdstippen, de combinatie van die twee technieken kan elkaar versterken. Bij sentiment mining weet je wel wat iemands zijn gevoelens zijn, maar niet zijn drijfveren, terwijl drijfveren juist een betere verklaring voor iemands gedrag vormen. De combinatie van deze technieken biedt mogelijkheden om nieuwe inzichten te verwerven rond customer journeys, zodat de klant uiteindelijk beter geholpen wordt." http://www.naf.nl/events/proces-text-mining/
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This method paper presents a template solution for text mining of scientific literature using the R tm package. Literature to be analyzed can be collected manually or automatically using the code provided with this paper. Once the literature is collected, the three steps for conducting text mining can be performed as outlined below:• loading and cleaning of text from articles,• processing, statistical analysis, and clustering, and• presentation of results using generalized and tailor-made visualizations.The text mining steps can be applied to a single, multiple, or time series groups of documents.References are provided to three published peer reviewed articles that use the presented text mining methodology. The main advantages of our method are: (1) Its suitability for both research and educational purposes, (2) Compliance with the Findable Accessible Interoperable and Reproducible (FAIR) principles, and (3) code and example data are made available on GitHub under the open-source Apache V2 license.
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In this article, we present CoPub 5.0, a publicly available text mining system, which uses Medline abstracts to calculate robust statistics for keyword co-occurrences. CoPub was initially developed for the analysis of microarray data, but we broadened the scope by implementing new technology and new thesauri. In CoPub 5.0, we integrated existing CoPub technology with new features, and provided a new advanced interface, which can be used to answer a variety of biological questions. CoPub 5.0 allows searching for keywords of interest and its relations to curated thesauri and provides highlighting and sorting mechanisms, using its statistics, to retrieve the most important abstracts in which the terms co-occur. It also provides a way to search for indirect relations between genes, drugs, pathways and diseases, following an ABC principle, in which A and C have no direct connection but are connected via shared B intermediates. With CoPub 5.0, it is possible to create, annotate and analyze networks using the layout and highlight options of Cytoscape web, allowing for literature based systems biology. Finally, operations of the CoPub 5.0 Web service enable to implement the CoPub technology in bioinformatics workflows. CoPub 5.0 can be accessed through the CoPub portal http://www.copub.org. © 2011 The Author(s).
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'The Data Tales' is een langdurig samenwerkingsverband van onderzoekers en bedrijven die samen projecten uitvoeren en vragen beantwoorden als: hoe kan data ons helpen de relatie met klanten te verbeteren en hoe beschermen we privacy van de klant als we die klant ook beter van dienst zijn willen zijn met data technieken?Doel The Data Tales consortium wil bedrijven helpen om beter met hun klanten om te gaan. Want als bedrijven naar hun klanten luisteren, versterken ze hun band. Techniek biedt allerlei opties om sneller, gerichter en zinvoller te reageren op de behoeften van klanten. Daarbij moeten de toon, inhoud en presentatie van de boodschap aansluiten bij de geadresseerde. Het doel van The Data Tales is om samen met onderwijs, bedrijven en technologie-ontwikkelaars te werken aan technieken om direct inzicht te geven in hoe hun klanten de interactie met organisaties ervaren. Daarbij wordt altijd gewerkt volgens het principe 'ethics by design' Resultaten Consortium The Data Tales vormde de basis voor het KIEM-project, VERBIND. Dat staat voor verantwoorde, belevingsgerichte interactie op basis van data-analyse. VERBIND brengt meerdere invalshoeken samen. We kijken niet alleen naar wat technisch mogelijk is bij dataverzameling, maar ook naar ethische keuzes die bedrijven maken. Op thedatatales.org lees je meer over het project VERBIND. Looptijd 01 januari 2018 - 31 december 2020 Aanpak In het Data Tales consortium komen de volgende vakgebieden samen: Customer Journey & marketing Data Science, waaronder process mining, text mining en andere vormen van data mining Recht en Ethiek, waaronder AVG Gedragswetenschappen ICT
Under the umbrella of artistic sustenance, I question the life of materials, subjective value structures, and working conditions underlying exhibition making through three interconnected areas of inquiry: Material Life and Ecological Impact — how to avoid the accumulation of physical materials/storage after exhibitions? I aim to highlight the provenance and afterlife of exhibition materials in my practice, seeking economic and ecological alternatives to traditional practices through sustainable solutions like borrowing, reselling, and alternative storage methods that could transform exhibition material handling and thoughts on material storage and circulation. Value Systems and Economic Conditions —what do we mean when we talk about 'value' in relation to art? By examining the flow of financial value in contemporary art and addressing the subjectivity of worth in art-making and artists' livelihoods, I question traditional notions of sculptural skill while advocating for recognition of conceptual labour. The research considers how artists might be compensated for the elegance of thought rather than just material output. Text as Archive and Speculation— how can text can store, speculate, and circulate the invisible labour and layers of exhibition making? Through titles, material lists, and exhibition texts, I explore writing's potential to uncover latent structures and document invisible labor, considering text both as an archiving method and a tool for speculating about future exhibitions. Using personal practice as a case study, ‘Conditions for Raw Materials’ seeks to question notions of value in contemporary art, develop alternative economic models, and make visible the material, financial, and relational flows within exhibitions. The research will manifest through international exhibitions, a book combining poetic auto-theoretical reflection with exhibition speculation, new teaching formats, and long-term investigations. Following “sticky relations," of intimacy, economy and conditions, each exhibition serves as a case study exploring exhibition making from emotional, ecological, and economic perspectives.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
