In the third part, we justify selected qualifications of globality and flexibility by the fact that Hadoop solutions enable comparable returns in opposite contexts of models of partial submodels and of models of final exact systems. With the rise of e-commerce, recommendation systems have become a very important factor in the success of business. Wine is the second most popular alcoholic drink in the world behind beer. The effectiveness of the proposed methodology has diligently been examined on numerous real-life social networks and proven superior to various similar approaches in terms of performance, stability, and accuracy. Specifically, using a distributed, stacking-based model, which is built on plain network topology characteristics of bootstrap sampled subgraphs, the underlined community hierarchy of any given social network is efficiently extracted in spite of its size and density. After having briefly recalled the strategic advantages of big data solutions in the introductory remarks, in the first part of this paper, we focus on the advantages of big data solutions in the currently difficult time of the COVID-19 pandemic. Despite various forms of bias, ultimately, risks result from eventual rule conflicts between the AI system behavior due to feature complexity and user practices with limited options for scrutiny. As experienced in former massive information issues, big data technologies, such as Hadoop, should. In this paper, we present GeoLOD, a web catalog of spatial datasets and classes and a recommender for spatial datasets and classes possibly relevant for link discovery processes. Recommendation systems analyze metadata to predict if, for example, a user will recommend a product. 0.778 Impact Factor 2019 Applicable Algebra in Engineering, Communication and Computing. Moreover, the management of finite resources. In this paper, we explore the effects of a new wine ontology in a recommendation system. In this article, we describe how such annotations may be integrated into different player profile clustering schemes derived from a template Simon–Ando iterative process. However, the existing algorithms principally propose iterative solutions of high polynomial order that repetitively require exhaustive analysis. IBM being the pioneer of this technology has invested $26 billion dollars in big data and analytics and now spends close to one-third of its R&D budget in developing cognitive computing technology. Big Data and Cognitive Computing, Volume 5; doi:10.3390/bdcc5010011. ... of Mathematics and Artificial Intelligence. Specifically, using a distributed, stacking-based model, which is built on plain network topology characteristics of bootstrap sampled subgraphs, the underlined community hierarchy of any given social network is efficiently extracted in spite of its size and density. With the rise of e-commerce, recommendation systems have become a very important factor in the success of business. Autopoietic machines use knowledge structures containing the behavioral evolution of the system and its interactions with the environment to maintain stability by counteracting fluctuations. In the results, we provide statistics about the status and potential connectivity of spatial datasets in the WoD, we assess the applicability of the recommender, and we present the outcome of a system usability study. Every year, plant diseases cause a significant loss of valuable food crops around the world. These results indicate the possibility of adapting inexpensive synthetic data merging with a certain amount of the experimental database for training the neural networks in order to achieve the compelling performance from a limited collection of the annotated experimental data of a real-world practical thermography experiment. 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