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Journal articles on the topic 'System Context'

Author: Grafiati

Published: 4 June 2025

Last updated: 23 June 2025

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1

Pisotskyi, Marian, and Alexey Botchkaryov. "Online Video Platform with Context-aware Content-based Recommender System." Advances in Cyber-Physical Systems 6, no. 1 (2021): 46–53. http://dx.doi.org/10.23939/acps2021.01.046.

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The problem of developing an online video platform with a context-aware content-based recommender system has been considered. Approaches to developing online video platforms have been considered. A comparison of popular online video platforms has been presented. A method of context-aware content-based recommendation of videos has been proposed. A method involves saving information about user interaction with video, obtaining and storing information about which videos the user liked, determining user context, composing a profile of user preferences, composing a profile of user preferences depending on context, determining the similarity between the video profile and a profile of user preferences (with and without context consideration), determining the relevance of the video to the context, the conclusive estimation of the relevance of the video to the user’s preferences based on the proposed composite relevance indicator. The developed structure of online video platform has been presented. The algorithm of its work has been considered. The structure of the online video platform database has been proposed. Features of designing the user interface of the online video platform have been considered. The issue of testing the developed online video platform has been considered.

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Kiani, Abdollah, Mohsen Amiri Fakhr, and Reza Rezaei. "Architectural Patterns for Context-Aware System." Journal of Software 10, no. 8 (2015): 1002–13. http://dx.doi.org/10.17706//jsw.10.8.1002-1013.

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Chernadchuk, Viktor, Viktor Sukhonos, and Inna Shkolnyk. "The notion and content of financial system in the context of financial law of Ukraine." Problems and Perspectives in Management 15, no. 2 (2017): 234–45. http://dx.doi.org/10.21511/ppm.15(2-1).2017.07.

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The financial system of the advanced countries develops according to two basic models – a bank-based system and a market-based system, depending on the level of protection of the rights of owners, investors and lenders. A paradigm shift in functioning of global financial system and financial systems of all countries is based on financial law, which formalizes all financial relations. Reviewing the financial system of Ukraine, the researchers pay a special attention to public finance due to its substantial share in redistribution of Ukraine’s GDP. A comparative analysis of the concept “financial system” makes it possible to draw a certain analogy with the approaches of experts in financial law. From the economic point of view, a country’s financial system includes three key areas – state finance, household finance and corporate finance, which are closely interrelated. Matching these three spheres with the legal approach, state finance is defined as public finance, while household finance and corporate finance are referred as private finance. The financial market functions as a part of the financial system. In economic terms, the financial system is a dynamic and open environment, while it implies an intense movement of financial resources, a rapid emergence of new financial instruments and integration into the global financial market. From the legal point of view, the financial system is a static financial and legal phenomenon, which includes centralized and decentralized public funds, as well as funds of business entities and individuals.

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El Guabassi, Inssaf, Zakaria Bousalem, Mohammed Al Achhab, Ismail JELLOULI, and Badr Eddine EL Mohajir. "Personalized adaptive content system for context-aware ubiquitous learning." Procedia Computer Science 127 (2018): 444–53. http://dx.doi.org/10.1016/j.procs.2018.01.142.

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Fatima, BiBi. "Education System in the Context of India." International Journal of Science and Research (IJSR) 11, no. 2 (2022): 951–53. http://dx.doi.org/10.21275/sr22222133722.

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KANG, H., E. SUH, and K. YOO. "Packet-based context aware system to determine information system user’s context." Expert Systems with Applications 35, no. 1-2 (2008): 286–300. http://dx.doi.org/10.1016/j.eswa.2007.06.033.

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Iqbal, Misbah, Mustansar Ali Ghazanfar, Asma Sattar, et al. "Kernel Context Recommender System (KCR): A Scalable Context-Aware Recommender System Algorithm." IEEE Access 7 (2019): 24719–37. http://dx.doi.org/10.1109/access.2019.2897003.

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Piątek, Radosław. "World Class Manufacturing, Toyota Manufacturing System: production system comparison in sustainability context." Nowoczesne Systemy Zarządzania 17, no. 4 (2022): 91–110. http://dx.doi.org/10.37055/nsz/158800.

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Systemy produkcyjne stanowią jeden z głównych filarów przedsiębiorstw. Ich wydajność i zasady funkcjonowania determinują finalną jakość produktów, których odbiorcami są instytucje oraz konsumenci końcowi. Jednak współcześnie oprócz wcześniej wymienionych zagadnień pojawiły się nowe wymagania związane z koncepcją zrównoważonego rozwoju. Metody produkcji, wpływ na środowisko naturalne czy poszanowanie ludzi stały się równie istotnymi aspektami jak trwałość lub cena produktu. Celem niniejsze-go artykułu jest przedstawienie porównania dwóch systemów produkcyjnych, które cieszą się dużą popularnością, zwłaszcza w przemyśle motoryzacyjnym, tj. Toyota Production System (TPS – System Produk-cyjny Toyoty) oraz World Class Manufacturing (WCM – Produkcja Klasy Światowej), w kontekście zrównoważonego rozwoju. W tym celu zrealizowano analizę porównawczą opartą na czterech kategoriach: skomplikowanie systemu, popularność, uniwersalność oraz powiązania ze zrównoważonym rozwojem. Zgromadzony materiał ma zróżnicowany charakter, co pozwala na głębokie spektrum badania i porównania obu rozwiązań. W wyniku przeprowadzonej analizy można zauważyć różnice w poziomie komplikacji obu rozwiązań produkcyjnych. System Produkcyjny Toyoty ma prostszą strukturę w porównaniu do Produkcji Klasy Światowej. Modelowe przedstawienie systemu TPS ukazuje wszystkie główne elementy wraz z ich najważniejszymi cechami i zastosowaniem. WCM jest systemem o bardziej skomplikowanej budo-wie, precyzującym większą liczbę czynników koniecznych do wdrożenia i utrzymania. W przypadku popularności obu rozwiązań przeprowadzone badanie ukazało, że częściej wyszukiwaną frazą jest Toyota Production System, ale większą liczbą publikacji i materiałów może się pochwalić World Class Manufacturing. Oba systemy są wysoce uniwersalnymi rozwiązaniami produkcyjnymi. Analizowane studia przypadków ukazują implementacje zakończone sukcesem w przedsiębiorstwach produkcyjnych i usługowych w branżach niezwiązanych z przemysłem motoryzacyjnym. Odnosząc się do zgodności z wyznacznikami zrównoważonego rozwoju, można stwierdzić, że oba systemy posiadają elementy odpowiedzialne za realizację wymienionych postanowień, ale realizują je w różny sposób. TPS nie wiąże się bezpośrednio z koncepcją zrównoważonego rozwoju, ale sam system ma w sobie zagadnienia skupione wokół redukcji strat, oszczędności, produkcji jedynie potrzebnych w danej chwili komponentów czy szacunku dla ludzi. WCM zaś ma specjalny element odpowiadający za realizację wymagań normy ISO 14000, która dotyczy zarządzania wpływem na środowisko naturalne. Finalnie można przyjąć, że oba systemy przejawiają wiele cech wspólnych, np. w przypadku założeń funkcjonowania jednak realizacja w każdym z nich ma inny charakter. TPS jest systemem prostszym, pozwalającym się łatwo dostosować do specyfiki organizacji. WCM jest systemem bardziej skomplikowanym, o dużym stopniu sformalizowania. Wykonana analiza ma charakter przeglądowy, ukazując możliwie szerokie spektrum obu systemów produkcyjnych. Istnieje możliwość dalszego realizowania badań dzięki poddawaniu bardziej szczegółowym analizom każdego z aspektów systemów lub zestawienia ich z innymi rozwiązaniami produkcyjnymi.

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R.R, Lekshmi. "Frequency Based Demand Management System in Residential Context." Bonfring International Journal of Industrial Engineering and Management Science 4, no. 2 (2014): 57–61. http://dx.doi.org/10.9756/bijiems.4815.

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El-Zawawy, Mohamed A. "Testing Automation of Context-Oriented Programs Using Separation Logic." Applied Computational Intelligence and Soft Computing 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/930186.

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A new approach for programming that enables switching among contexts of commands during program execution is context-oriented programming (COP). This technique is more structured and modular than object-oriented and aspect-oriented programming and hence more flexible. For context-oriented programming, as implemented in COP languages such as ContextJ*and ContextL, this paper introduces accurate operational semantics. The language model of this paper uses Java concepts and is equipped with layer techniques for activation/deactivation of layer contexts. This paper also presents a logical system for COP programs. This logic is necessary for the automation of testing, developing, and validating of partial correctness specifications for COP programs and is an extension of separation logic. A mathematical soundness proof for the logical system against the proposed operational semantics is presented in the paper.

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11

Liang, Chao, Changsheng Xu, and Hanqing Lu. "Personalized Sports Video Customization Using Content and Context Analysis." International Journal of Digital Multimedia Broadcasting 2010 (2010): 1–20. http://dx.doi.org/10.1155/2010/836357.

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We present an integrated framework on personalized sports video customization, which addresses three research issues: semantic video annotation, personalized video retrieval and summarization, and system adaptation. Sports video annotation serves as the foundation of the video customization system. To acquire detailed description of video content, external web text is adopted to align with the related sports video according to their semantic correspondence. Based on the derived semantic annotation, a user-participant multiconstraint 0/1 Knapsack model is designed to model the personalized video customization, which can unify both video retrieval and summarization with different fusion parameters. As a measure to make the system adaptive to the particular user, a social network based system adaptation algorithm is proposed to learn latent user preference implicitly. Both quantitative and qualitative experiments conducted on twelve broadcast basketball and football videos validate the effectiveness of the proposed method.

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Rudy, J. W. "Context representations, context functions, and the parahippocampal-hippocampal system." Learning & Memory 16, no. 10 (2009): 573–85. http://dx.doi.org/10.1101/lm.1494409.

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13

Oluwatimi, Oyindamola, Maria Luisa Damiani, and Elisa Bertino. "A context-aware system to secure enterprise content: Incorporating reliability specifiers." Computers & Security 77 (August 2018): 162–78. http://dx.doi.org/10.1016/j.cose.2018.04.001.

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Yaici, Malika, Anis Oussayah, and Mohamed Ahmed Takerrabet. "Trust-based Context-aware Authentication System for Ubiquitous Systems." Procedia Computer Science 134 (2018): 35–42. http://dx.doi.org/10.1016/j.procs.2018.07.141.

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Hiang, TEO Siow, and NG Chu Ngah. "5.2.1 Understanding “System-of-Systems” in the Defense Context." INCOSE International Symposium 21, no. 1 (2011): 559–68. http://dx.doi.org/10.1002/j.2334-5837.2011.tb01225.x.

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An, Tae-Ki, and Moon-Hyun Kim. "Context-aware Video Surveillance System." Journal of Electrical Engineering and Technology 7, no. 1 (2012): 115–23. http://dx.doi.org/10.5370/jeet.2012.7.1.115.

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Sheela, J. D. Emerald Princess, and V. Thanga Murugeshwari. "Context-free graph P system." International Journal of Artificial Intelligence and Soft Computing 7, no. 1 (2019): 86. http://dx.doi.org/10.1504/ijaisc.2019.10026571.

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Murugeshwari, V. Thanga, and J. D. Emerald Princess Sheela. "Context-free graph P system." International Journal of Artificial Intelligence and Soft Computing 7, no. 1 (2019): 86. http://dx.doi.org/10.1504/ijaisc.2019.105021.

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19

Alghamdi, Wael, Elhadi Shakshuki, and Tarek R.Sheltami. "Context-Aware Driver Assistance System." Procedia Computer Science 10 (2012): 785–94. http://dx.doi.org/10.1016/j.procs.2012.06.100.

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20

Chatterjee, Amitabha. "Preserved Context Index System (Precis)." KNOWLEDGE ORGANIZATION 51, no. 2 (2024): 127–45. http://dx.doi.org/10.5771/0943-7444-2024-2-127.

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This article discusses the genesis and development of PRECIS Indexing System, its syntax and semantics, different formats and structure, and the primary notions underlying the system. It further explains how index entries are generated through a simple mechanical process called ‘shunting’. The merits and criticisms of the system and its application across countries, across languages and across media have also been discussed. Finally, its relevance and workability in the online environment have been examined.

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Azri, Muhammad Haziq Fikri Bin, Su-Cheng Haw, Kok-Why Ng, and Mohamad Firdaus Mat Saad. "Context-Aware Job Recommender System." JOIV : International Journal on Informatics Visualization 9, no. 2 (2025): 877. https://doi.org/10.62527/joiv.9.2.3021.

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Context-aware recommendation systems have emerged as essential to interactive web content and online job search. Primarily, since so many job offers are published on different online platforms, it can make the users take some time to find good opportunities that match exactly what they are looking for, as well as countless qualified candidates and other characteristics within that context, such as temporality. This comes as no surprise, as many practitioners and researchers have resorted to machine learning to create context-aware job recommendation systems that cater not only to job seekers. In this comparative paper, we have analyzed various machine-learning models for job recommendation systems. Four fundamental pillars are considered: accuracy, scalability, interpretability, and computational efficiency. This paper also studies the extent to which these models are contextual (e.g., how well they can model factors due to user preferences, job requirements, location, industry evolution, and temporality.) and can be used as a recommendation system. This study uses real-world employment data from actual employment statistics (through fixed-period analysis), professional networking platforms, and online job market platforms. The study does so purposefully to be comprehensive because it believes the lessons from remote work are generalizable. Still, the data is from a wide variety of job sectors, job positions, and locations. The group created a test environment for constructing and testing machine learning algorithms. Collaborative filtering, content-based, matrix factorization, deep learning, and many other hybrid approaches have obtained better results. This study was performed on Python with sci-kit-learn, pandas, and NumPy. The proposed system is a context-aware job recommender system that employs many machine learning algorithms to personalize job recommendations concerning user preferences and contextual information such as job location, industry status, and temporal dynamics. The findings underscore the importance of choosing machine learning models that are well-suited for job recommendation systems on a case-by-case basis. This comparative study intends to add to the art by providing algorithmic proof and practical advice to properly leverage machine learning models proposed in a naturalistic, messy setting of context-aware job recommendation systems.

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Zagata, L. "Bio cash-cow? Context and content of Czech organic farming." Agricultural Economics (Zemědělská ekonomika) 53, No. 1 (2008): 45–53. http://dx.doi.org/10.17221/993-agricecon.

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This work presents results of a qualitative empirical study on practices of farmers participating in the Czech system of organic agriculture (ecological agriculture). Growth of this sector has been seen almost solely in positive terms, without questioning its content. However, Czech organic agriculture does not stem from the organic movement as is the case in Western Europe and therefore it is necessary to ask what it draws on and to discover, with regard to its nature, whether it can meet the expectations stated in official policies. This paper briefly describes the development of organic farming in other countries and the current problem of its conventionalization. The research study then shows evidence that organic farming is not adopted only because of stateÃ¢ÂÂs subsidies, but also due to the specific value orientation of farmers, despite the history and the lack of tradition of these specific practices in the Czech Republic.

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Javed, Umair, Kamran Shaukat, Ibrahim A. Hameed, Farhat Iqbal, Talha Mahboob Alam, and Suhuai Luo. "A Review of Content-Based and Context-Based Recommendation Systems." International Journal of Emerging Technologies in Learning (iJET) 16, no. 03 (2021): 274. http://dx.doi.org/10.3991/ijet.v16i03.18851.

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In our work, we have presented two widely used recommendation systems. We have presented a context-aware recommender system to filter the items associated with user’s interests coupled with a context-based recommender system to prescribe those items. In this study, context-aware recommender systems perceive the user’s location, time, and company. The context-based recommender system retrieves patterns from World Wide Web-based on the user’s past interactions and provides future news recommendations. We have presented different techniques to support media recommendations for smartphones, to create a framework for context-aware, to filter E-learning content, and to deliver convenient news to the user. To achieve this goal, we have used content-based, collaborative filtering, a hybrid recommender system, and implemented a Web ontology language (OWL). We have also used the Resource Description Framework (RDF), JAVA, machine learning, semantic mapping rules, and natural ontology languages that suggest user items related to the search. In our work, we have used E-paper to provide users with the required news. After applying the semantic reasoning approach, we have concluded that by some means, this approach works similarly as a content-based recommender system since by taking the gain of a semantic approach, we can also recommend items according to the user’s interests. In a content-based recommender system, the system provides additional options or results that rely on the user’s ratings, appraisals, and interests.

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Lahlou, Fatima Zahra, Houda Benbrahim, and Ismail Kassou. "Review Aware Recommender System." International Journal of Distributed Artificial Intelligence 10, no. 2 (2018): 28–50. http://dx.doi.org/10.4018/ijdai.2018070102.

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Context aware recommender systems (CARS) are recommender systems (RS) that provide recommendations according to user contexts. The first challenge for building such a system is to get the contextual information. Some works tried to get this information from reviews provided by users in addition to their ratings. However, all of these works perform important feature engineering in order to infer the context. In this article, the authors present a new CARS architecture that allows to automatically use contextual information from reviews without requiring any feature engineering. Moreover, they develop a new CARS algorithm that is tailored to textual contexts, that they call Textual Context Aware Factorization Machines (TCAFM). An empirical evaluation shows that the proposed architecture allows to significantly improve recommendation accuracy using state of the art RS and CARS algorithms, whereas TCAFM leads to additional improvements.

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Ko, Kwang-Eun, and Kwee-Bo Sim. "Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling." International Journal of Fuzzy Logic and Intelligent Systems 8, no. 4 (2008): 254–59. http://dx.doi.org/10.5391/ijfis.2008.8.4.254.

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Cambria, Erik, and Amir Hussain. "Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System." Cognitive Computation 4, no. 4 (2012): 477–96. http://dx.doi.org/10.1007/s12559-012-9145-4.

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27

Jing, Nan. "Skyguard: A Context-Aware Mobile Information System for Emergency Management." International Journal of Machine Learning and Computing 5, no. 1 (2015): 44–50. http://dx.doi.org/10.7763/ijmlc.2015.v5.481.

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De la Fuente Robles, Yolanda, and Eva Sotomayor Morales. "The Spanish Long-Term Care System in the European Context." Arbor 191, no. 771 (2015): a206. http://dx.doi.org/10.3989/arbor.2015.771n1008.

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PRISACARIU, Vasile, and Adrian MURARU. "UNMANNED AERIAL SYSTEM (UAS) IN THE CONTEXT OF MODERN WARFARE." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (2016): 177–84. http://dx.doi.org/10.19062/2247-3173.2016.18.1.23.

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Qassimi, Sara, El Hassan Abdelwahed, and Meriem Hafidi. "Folksonomy Graphs Based Context-Aware Recommender System Using Spectral Clustering." International Journal of Machine Learning and Computing 10, no. 1 (2020): 63–68. http://dx.doi.org/10.18178/ijmlc.2020.10.1.899.

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Lin, Cheng‐Jian, and Chi‐Nan Tsai. "Using context‐sensitive neuro‐fuzzy systems for nonlinear system identification." Journal of the Chinese Institute of Engineers 27, no. 1 (2004): 1–8. http://dx.doi.org/10.1080/02533839.2004.9670844.

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Al-Sultan, Saif, Ali H. Al-Bayatti, and Hussein Zedan. "Context-Aware Driver Behavior Detection System in Intelligent Transportation Systems." IEEE Transactions on Vehicular Technology 62, no. 9 (2013): 4264–75. http://dx.doi.org/10.1109/tvt.2013.2263400.

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Nilsson, Robert, Dov Dori, Yatin Jayawant, Leonard Petnga, Hanan Kohen, and Michael Yokell. "Towards an Ontology for Collaboration in System of Systems Context." INCOSE International Symposium 30, no. 1 (2020): 666–79. http://dx.doi.org/10.1002/j.2334-5837.2020.00747.x.

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VUJOVIĆ, Novica. "MODERN SCHOOL CURRICULA IN THE CONTEXT OF DIALECTOLOGY CONTENT." Lingua Montenegrina 32, no. 2 (2023): 3–17. https://doi.org/10.46584/lm.v32i2.1003.

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In this paper, we review school curricula and Montenegrin language textbooks from the point of view of representation and treatment of Montenegrin dialects or traditional elements content implemented in one of our micro-dialect types. We believe that Montenegrin dialects, in terms of dialectology, sociolinguistics, and linguistic culture, offer important information to the national culture in many respects, and that they should be valued as part of the intangible cultural heritage. We state that the reformed latest curricula and Montenegrin language textbooks offer a valuable basis for evaluating and affirming these contents. The problem that slows down this process relates to the remaining traditionalist approach to the Montenegrin language and non-standard idioms both in Montenegrin education system and in public discourse as a whole, so well-conceived curricula and affirmation of Montenegrin dialects as intangible cultural heritage is imposed as a necessity. In this endeavour, the educational system has a fundamental role.

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K., G., and Y. K. "Context based GIS Location Information System." International Journal of Computer Applications 160, no. 5 (2017): 38–40. http://dx.doi.org/10.5120/ijca2017913054.

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Kiani, Abdollah, Mohsen Amiri Fakhr, and Reza Rezaei. "Architectural Patterns for Context-Aware System." Journal of Software 10, no. 8 (2015): 1002–13. http://dx.doi.org/10.17706/jsw.10.8.1002-1013.

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Le, Tiep, Tran Cao Son, and Enrico Pontelli. "Multi-Context System for Optimization Problems." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 2929–37. http://dx.doi.org/10.1609/aaai.v33i01.33012929.

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This paper proposes Multi-context System for Optimization Problems (MCS-OP) by introducing conditional costassignment bridge rules to Multi-context Systems (MCS). This novel feature facilitates the definition of a preorder among equilibria, based on the total incurred cost of applied bridge rules. As an application of MCS-OP, the paper describes how MCS-OP can be used in modeling Distributed Constraint Optimization Problems (DCOP), a prominent class of distributed optimization problems that is frequently employed in multi-agent system (MAS) research. The paper shows, by means of an example, that MCS-OP is more expressive than DCOP, and hence, could potentially be useful in modeling distributed optimization problems which cannot be easily dealt with using DCOPs. It also contains a complexity analysis of MCS-OP.

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Lee, Kahyun, Mehmet Kayaalp, Sam Henry, and Özlem Uzuner. "A Context-Enhanced De-identification System." ACM Transactions on Computing for Healthcare 3, no. 1 (2022): 1–14. http://dx.doi.org/10.1145/3470980.

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Many modern entity recognition systems, including the current state-of-the-art de-identification systems, are based on bidirectional long short-term memory (biLSTM) units augmented by a conditional random field (CRF) sequence optimizer. These systems process the input sentence by sentence. This approach prevents the systems from capturing dependencies over sentence boundaries and makes accurate sentence boundary detection a prerequisite. Since sentence boundary detection can be problematic especially in clinical reports, where dependencies and co-references across sentence boundaries are abundant, these systems have clear limitations. In this study, we built a new system on the framework of one of the current state-of-the-art de-identification systems, NeuroNER, to overcome these limitations. This new system incorporates context embeddings through forward and backward n -grams without using sentence boundaries. Our context-enhanced de-identification (CEDI) system captures dependencies over sentence boundaries and bypasses the sentence boundary detection problem altogether. We enhanced this system with deep affix features and an attention mechanism to capture the pertinent parts of the input. The CEDI system outperforms NeuroNER on the 2006 i2b2 de-identification challenge dataset, the 2014 i2b2 shared task de-identification dataset, and the 2016 CEGS N-GRID de-identification dataset ( p &#x003C; 0.01 ). All datasets comprise narrative clinical reports in English but contain different note types varying from discharge summaries to psychiatric notes. Enhancing CEDI with deep affix features and the attention mechanism further increased performance.

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Pouryegan, Mohammad, and Mohammad Reza Malek. "A context-aware pedestrian navigation system." Journal of Ambient Intelligence and Smart Environments 7, no. 4 (2015): 415–24. http://dx.doi.org/10.3233/ais-150332.

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Gaude, Reshabh. "Context Attentive Recommender System: A Survey." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (2019): 1123–25. http://dx.doi.org/10.22214/ijraset.2019.6193.

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Ущаповський, Юрій Володимирович. "Structure of economic system: institutional context." Journal of Zhytomyr State Technological University. Series: Economics, Management and Administration, no. 4 (86) (December 29, 2018): 20–24. http://dx.doi.org/10.26642/jen-2018-4(86)-20-24.

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Hecht, Herbert, and Myron Hecht. "Software reliability in the system context." IEEE Transactions on Software Engineering SE-12, no. 1 (1986): 51–58. http://dx.doi.org/10.1109/tse.1986.6312919.

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Yared, Rami, and Bessam Abulrazak. "Adaptable Context-Aware Cooking-Safe System." IEEE Transactions on Services Computing 11, no. 2 (2018): 236–48. http://dx.doi.org/10.1109/tsc.2017.2662941.

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Stefanidis, Kostas, Evaggelia Pitoura, and Panos Vassiliadis. "A context‐aware preference database system." International Journal of Pervasive Computing and Communications 3, no. 4 (2008): 439–60. http://dx.doi.org/10.1108/17427370710863158.

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Rasekh, Mohammad. "The Iranian Constitutional System in Context." Yearbook of Islamic and Middle Eastern Law Online 12, no. 1 (2005): 69–96. http://dx.doi.org/10.1163/22112987-91000125.

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Stephen Morris and Hyun Song Shin. "Financial Regulation in a System Context." Brookings Papers on Economic Activity 2008, no. 2 (2009): 229–74. http://dx.doi.org/10.1353/eca.0.0023.

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Jung, Hwa Young, Jae Wook Park, and Yong Kyu Lee. "A Context-Aware Treatment Guidance System." Journal of the Korea Society of Computer and Information 19, no. 1 (2014): 141–48. http://dx.doi.org/10.9708/jksci.2014.19.1.141.

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Bukola, Olubadeji, Adetunmbi A.O, and Alese B.K. "DCA as Context (Environment) Sensitive System." International Journal of Computer Applications 131, no. 1 (2015): 39–46. http://dx.doi.org/10.5120/ijca2015907236.

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Castro, G. G., E. L. Dominguez, Y. H. Velazquez, M. Y. R. Matla, C. B. E. Toledo, and S. E. P. Hernandez. "MobiLearn: Context-Aware Mobile Learning System." IEEE Latin America Transactions 14, no. 2 (2016): 958–64. http://dx.doi.org/10.1109/tla.2016.7437246.

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Dionne, Guy. "PRECIS I: Preserved Context Indexing System." Documentation et bibliothèques 21, no. 1 (2019): 9–21. http://dx.doi.org/10.7202/1055515ar.

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Abstract:

Ce texte retrace rapidement l’évolution des travaux qui ont servi de base à l’établissement de PRECIS I, tel qu’il a été utilisé par la British National Bibliography de janvier 1971 jusqu’à décembre 1973. Suivent 10 notices catalographiques accompagnées de l’analyse française des sujets avant input, avec, en plus, des entrées d’index telles qu’elles apparaîtraient après le traitement automatique. Une bibliographie termine l’article.

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