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Journal articles on the topic 'RecSys'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

An, Yiquan, Yingxin Tan, Xi Sun, and Giovannipaolo Ferrari. "Recommender System: A Comprehensive Overview of Technical Challenges and Social Implications." IECE Transactions on Sensing, Communication, and Control 1, no. 1 (2024): 30–51. http://dx.doi.org/10.62762/tscc.2024.898503.

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The proliferation of Recommender Systems (RecSys), driven by their expanding application domains, explosive data growth, and exponential advancements in computing capabilities, has cultivated a dynamic and evolving research landscape. This paper comprehensively reviews the foundational concepts, methodologies, and challenges associated with RecSys from technological and social scientific lenses. Initially, it categorizes personalized RecSys technical solutions into five paradigms: collaborative filtering, scenario-aware, knowledge & data co-driven approaches, large language models, and hyb

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Bogers, Toine, Marijn Koolen, and Iván Cantador. "Report on RecSys 2014." ACM SIGIR Forum 49, no. 1 (2015): 20–26. http://dx.doi.org/10.1145/2795403.2795411.

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Said, Alan. "A Short History of the RecSys Challenge." AI Magazine 37, no. 4 (2017): 102–4. http://dx.doi.org/10.1609/aimag.v37i4.2693.

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The RecSys Challenge is a yearly recurring competition focusing on creating the best performing recommendation approach for a specific scenario. Over the years, the competition has drawn many participants from industry and academia, and has become an key part of the ACM Conference on Recommender Systems series. This article presents a brief historical overview of the RecSys Challenge from its inception in 2010 until the seventh iteration in 2016.

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Margaris, Dionisis, Kiriakos Sgardelis, Dimitris Spiliotopoulos, and Costas Vassilakis. "Exploiting Rating Prediction Certainty for Recommendation Formulation in Collaborative Filtering." Big Data and Cognitive Computing 8, no. 6 (2024): 53. http://dx.doi.org/10.3390/bdcc8060053.

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Collaborative filtering is a popular recommender system (RecSys) method that produces rating prediction values for products by combining the ratings that close users have already given to the same products. Afterwards, the products that achieve the highest prediction values are recommended to the user. However, as expected, prediction estimation may contain errors, which, in the case of RecSys, will lead to either not recommending a product that the user would actually like (i.e., purchase, watch, or listen) or to recommending a product that the user would not like, with both cases leading to

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Sun, Aixin. "Beyond Collaborative Filtering: A Relook at Task Formulation in Recommender Systems." ACM SIGWEB Newsletter 2024, Spring (2024): 1–11. http://dx.doi.org/10.1145/3663752.3663756.

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Recommender Systems (RecSys) have become indispensable in numerous applications, profoundly influencing our everyday experiences. Despite their practical significance, academic research in RecSys often abstracts the formulation of research tasks from real-world contexts, aiming for a clean problem formulation and more generalizable findings. However, it is observed that there is a lack of collective understanding in RecSys academic research. The root of this issue may lie in the simplification of research task definitions, and an overemphasis on modeling the decision outcomes rather than the d

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Zheng, Yong, Hanna Hauptmann, and Guibing Guo. "ACM Conference on Recommender Systems September 18--22, 2023 at Singapore." ACM SIGWEB Newsletter 2023, Summer (2023): 1–4. http://dx.doi.org/10.1145/3609429.3609431.

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ACM Conference on Recommender Systems (RecSys) is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. RecSys 2023 will be held in Singapore and will bring together the major international research groups working on recommender systems, along with many of the world's leading companies active in e-commerce and other adjacent domains. It is a SIGCHI-sponsored conference, that will attract also several leading industry sponsors. The proceedings will be published by ACM as part of the ACM Digital Library.

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Kristensen, Alexander, and Der Berg Charlotte Van. "Enhancing Energy Sector E-Commerce Data Storage through Distributed File Systems and Cloud Solutions." Academic Journal of Sociology and Management 2, no. 4 (2024): 35–40. https://doi.org/10.5281/zenodo.12747432.

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Recommender Systems (RecSys) play a crucial role in managing information overload and enhancing user satisfaction across various digital platforms, including e-commerce and entertainment. Evolving from traditional models to Deep Neural Networks (DNNs) and more recently, Large Language Models (LLMs), these systems leverage sophisticated algorithms to analyze user behaviors and preferences. LLMs, such as GPT-4, are trained on extensive datasets to comprehend and generate natural language, significantly advancing their ability to deliver personalized recommendations. This tutorial explores the tr

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Pham, Xuan, Jason Jung, and Ngoc Nguyen. "Integrating Multiple Experts for Correction Process in InteractiveRecommendation Systems." JUCS - Journal of Universal Computer Science 19, no. (4) (2013): 581–99. https://doi.org/10.3217/jucs-019-04-0581.

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User rating is obviously considered to be an important type of feedback informationfor Interactive Recommendation System (RecSys). The quality and credibility of user ratings will eventually influence the quality of recommendation. However, in the real world, there areusually many inconsistent (e.g., mistakes and missing values) or incorrect user ratings. Therefore, expert-based recommendation framework has been studied to select the most relevant expertsregarding a certain item's attribute (or value). This kind of RecSys can i) discover user preferenceand ii) determine a set of experts based

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Graus, David, Toine Bogers, Mesut Kaya, Francisco Gutiérrez, and Katrien Verbert. "Report on the 1st workshop on recommender systems for human resources (RecSys in HR 2021) at RecSys 2021." ACM SIGIR Forum 55, no. 2 (2021): 1–14. http://dx.doi.org/10.1145/3527546.3527567.

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Recommender systems are increasingly used in more high risk application domains, including in the domain of Human Resources (HR). These recommender systems help end-users find relevant vacancies out of an abundant overload of available vacancies, but also support other important objectives such as job mobility. Despite the use in industry applications, there are several research challenges associated to such objectives that have not yet been addressed in detail in this context, such as supporting end-users to steer the recommendation process with input and feedback and increasing diversity of

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Wang, Cheng, Mathias Niepert, and Hui Li. "RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems." IEEE Transactions on Neural Networks and Learning Systems 31, no. 8 (2020): 2731–40. http://dx.doi.org/10.1109/tnnls.2019.2907430.

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Chua, Tat-Seng. "Towards Generative Search and Recommendation: A keynote at RecSys 2023." ACM SIGIR Forum 57, no. 2 (2023): 1–14. http://dx.doi.org/10.1145/3642979.3642986.

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The emergence of large language models (LLM's), especially ChatGPT, has for the first time make AI known to almost everyone and affected every facet of our society. The LLMs have the potential to revolutionize the ways we seek and consume information. This has stemmed the recent trends in both academia and industry to develop LLM-based generative AI systems for various applications with enhanced capabilities. One such systems is the generative search and recommender system, which is capable of performing content retrieval, content repurposing, content creation and their integration to meet use

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Saw, Raj Kumar, Sumit Kumar, and Nidhi Mishra. "Music Recommendation System Using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 2804–8. http://dx.doi.org/10.22214/ijraset.2023.50754.

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Abstract: As part of this study, we present a music recommendation system that makes use of deep learning. The system learns a neural network that can anticipate the user's musical preferences and provide personalised playlist suggestions based on the user's listening habits. The proposed method considers both the user's explicit tastes and those that may be deduced from their listening patterns. The technology is able to adapt to a user's evolving preferences over time and provide more relevant recommendations. Software that predicts what a user will wish to buy based on their tastes and prio

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Azeroual, Otmane, and Tibor Koltay. "RecSys Pertaining to Research Information with Collaborative Filtering Methods: Characteristics and Challenges." Publications 10, no. 2 (2022): 17. http://dx.doi.org/10.3390/publications10020017.

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Recommendation (recommender) systems have played an increasingly important role in both research and industry in recent years. In the area of publication data, for example, there is a strong need to help people find the right research information through recommendations and scientific reports. The difference between search engines and recommendation systems is that search engines help us find something we already know, while recommendation systems are more likely to help us find new items. An essential function of recommendation systems is to support users in their decision making. Recommendat

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Bogers, Toine, Marijn Koolen, Cataldo Musto, Pasquale Lops, and Giovanni Semeraro. "Report on RecSys 2016Workshop on New Trends in Content-Based Recommender Systems." ACM SIGIR Forum 51, no. 1 (2017): 45–51. http://dx.doi.org/10.1145/3130332.3130341.

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Bunnell, Lawrence, Kweku-Muata Osei-Bryson, and Victoria Y. Yoon. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers." Information Systems Frontiers 22, no. 6 (2019): 1377–418. http://dx.doi.org/10.1007/s10796-019-09935-9.

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Yuan, Jing, Shaojie Tang, Shuzhang Cai, and Yao Wang. "Responsible RecSys by Design: Approximation Algorithms for Calibrated Recommendations with Sponsored Items." Proceedings of the International AAAI Conference on Web and Social Media 19 (June 7, 2025): 2197–209. https://doi.org/10.1609/icwsm.v19i1.35928.

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Calibrated Recommendation Systems (CRS) balance user preferences with constraints like diversity, fairness, and novelty to create inclusive recommendation lists. However, existing research often overlooks the mandatory inclusion of sponsored items, assuming unrestricted product selection. In practice, sponsored items, paid for by advertisers, must be included, which can conflict with CRS goals when advertisers' priorities misalign with system objectives. This paper addresses this gap by formulating CRS with sponsored items as a combinatorial optimization problem. We develop efficient approxima

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Said, Alan, Eva Zangerle, and Christine Bauer. "Report on the 3rd Workshop on the Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2023) at RecSys 2023." ACM SIGIR Forum 57, no. 2 (2023): 1–4. http://dx.doi.org/10.1145/3642979.3643000.

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Evaluation is a central step when developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2023 workshop, held as part of the 17th ACM Conference on Recommender Systems (RecSys 2023), served as a forum where researchers from both academia and industry critically reflected on the evaluation of recommender systems. The goal of the PERSPECTIVES workshop series is to capture the current state of evaluation from different perspectives and discuss the different targets that recommender systems evaluation should strive for. In the third edition of the workshop, we discussed problem

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Bogers, Toine, and Marijn Koolen. "Report on RecSys 2015 Workshop on New Trends in Content-Based Recommender Systems." ACM SIGIR Forum 49, no. 2 (2016): 141–46. http://dx.doi.org/10.1145/2888422.2888445.

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Anelli, Vito Walter, Pierpaolo Basile, Toine Bogers, et al. "Report on the 3rd workshop of knowledge-aware and conversational recommender systems (KARS/ComplexRec) at RecSys 2021." ACM SIGIR Forum 55, no. 2 (2021): 1–9. http://dx.doi.org/10.1145/3527546.3527566.

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In this report, we offer a brief overview of the contributions and takeaways from the Joint KaRS & ComplexRec Workshop, co-located with the 15 th edition of the ACM RecSys in Amsterdam, The Netherlands. With this workshop, we aimed to merge the main objectives envisioned for the 3 rd Edition of the Workshop of Knowledge-aware and Conversational Recommender Systems and the 5 th Edition of the Workshop on Recommendation in Complex Environments. This joint workshop adopted a hybrid format aligned with the goal of this year's main conference congregating to continue to build community around r

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Pera, Maria Soledad, Jerry Alan Fails, Mirko Gelsomini, and Franca Garzotto. "Building Community: Report on KidRec Workshop on Children and Recommender Systems at RecSys 2017." ACM SIGIR Forum 52, no. 1 (2018): 153–61. http://dx.doi.org/10.1145/3274784.3274803.

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Dacrema, Maurizio Ferrari, Pablo Castells, Justin Basilico, and Paolo Cremonesi. "Report on the Workshop on Learning and Evaluating Recommendations with Impressions (LERI) at RecSys 2023." ACM SIGIR Forum 57, no. 2 (2023): 1–8. http://dx.doi.org/10.1145/3642979.3643001.

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The Workshop on Learning and Evaluating Recommendations with Impressions (LERI) was held in conjunction with the 17th ACM Conference on Recommender Systems (RecSys 2023). The program included a keynote, a panel discussion and 7 paper presentations. The proceedings of the workshop are available online.1 The LERI workshop focused on all aspects related to the use of impressions for recommendation with the aim to bring the community together and share experience and perspectives. Recommender systems typically rely on past user interactions as the primary source of information for making predictio

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Zamani, Hamed, Markus Schedl, Paul Lamere, and Ching-Wei Chen. "An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation." ACM Transactions on Intelligent Systems and Technology 10, no. 5 (2019): 1–21. http://dx.doi.org/10.1145/3344257.

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Siddique, Muhammad Talha, Paraskevas Koukaras, Dimosthenis Ioannidis, and Christos Tjortjis. "SmartBuild RecSys: A Recommendation System Based on the Smart Readiness Indicator for Energy Efficiency in Buildings." Algorithms 16, no. 10 (2023): 482. http://dx.doi.org/10.3390/a16100482.

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The Smart Readiness Indicator (SRI) is a newly developed framework that measures a building’s technological readiness to improve its energy efficiency. The integration of data obtained from this framework with data derived from Building Information Modeling (BIM) has the potential to yield compelling results. This research proposes an algorithm for a Recommendation System (RS) that uses SRI and BIM data to advise on building energy-efficiency improvements. Following a modular programming approach, the proposed system is split into two algorithmic approaches linked with two distinct use cases.

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Kille, Benjamin, Andreas Lommatzsch, Özlem Özgöbek, Peng Liu, Lemei Zhang, and Simen Eide. "Report on the 11th International Workshop on News Recommendation and Analytics (INRA 2023) at ACM RecSys 2023." ACM SIGIR Forum 57, no. 2 (2023): 1–4. http://dx.doi.org/10.1145/3642979.3642997.

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News remains a challenging domain for personalization. INRA'23 allowed experts and practitioners to get together and discuss recent trends and future directions. Peer review selected six contributions for presentation covering a wide array of topics including beyond accuracy evaluation, the use of large language models, misinformation, and emotions in news. Date : 18 September 2023. Website : https://research.idi.ntnu.no/NewsTech/INRA/.

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Zangerle, Eva, Christine Bauer, and Alan Said. "Report on the 1st workshop on the perspectives on the evaluation of recommender systems (PERSPECTIVES 2021) at RecSys 2021." ACM SIGIR Forum 55, no. 2 (2021): 1–5. http://dx.doi.org/10.1145/3527546.3527565.

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Evaluation is a central step when it comes to developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2021 workshop at the 15th ACM Conference on Recommender Systems brought together academia and industry to critically reflect on the evaluation of recommender systems. The primary goal of the workshop was to capture the current state of evaluation from different, and maybe even diverging or contradictory perspectives. Date : 25 and 30 September 2021. Website : https://perspectives-ws.github.io/2021/.

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Zangerle, Eva, Christine Bauer, and Alan Said. "Report on the 2nd Workshop on the Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2022) at RecSys 2022." ACM SIGIR Forum 56, no. 2 (2022): 1–4. http://dx.doi.org/10.1145/3582900.3582919.

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Evaluation is a central step when it comes to developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2022 workshop at the 16th ACM Conference on Recommender Systems brought together academia and industry to critically reflect on the evaluation of recommender systems. The primary goal of the workshop was to capture the current state of evaluation from different, and maybe even diverging or contradictory perspectives. Date: 22 September, 2022. Website: https://perspectives-ws.github.io/2022/.

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Mansoury, Masoud. ""Understanding and mitigating multi-sided exposure bias in recommender systems" by Masoud Mansoury with Aparna S. Varde as coordinator." ACM SIGWEB Newsletter, Autumn (September 2022): 1–4. http://dx.doi.org/10.1145/3566100.3566103.

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Masoud Mansoury is a postdoctoral researcher at Amsterdam Machine Learning Lab at University of Amsterdam, Netherlands. He is also a member of Discovery Lab collaborating with Data Science team at Elsevier Company in the area of recommender systems. Masoud received his PhD in Computer and Information Science from Eindhoven University of Technology, Netherlands, in 2021. He has published his research works in top conferences such as FAccT, RecSys, and CIKM. His research interests include recommender systems, algorithmic bias, and contextual bandits. This research conducted by Masoud Mansoury in

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Ouyang, Zhongyu, Chunhui Zhang, Yaning Jia, and Soroush Vosoughi. "Scaled Supervision is an Implicit Lipschitz Regularizer." Proceedings of the International AAAI Conference on Web and Social Media 19 (June 7, 2025): 1419–35. https://doi.org/10.1609/icwsm.v19i1.35880.

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In modern social media, recommender systems (RecSys) rely on the click-through rate (CTR) as the standard metric to evaluate user engagement. CTR prediction is traditionally framed as a binary classification task to predict whether a user will interact with a given item. However, this approach overlooks the complexity of real-world social modeling, where user, item, and their interactive features change dynamically in fast-paced online environments. This dynamic nature often leads to model instability, reflected in overfitting short-term fluctuations rather than higher-level interactive patter

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Brusilovsky, Peter, Marco de Gemmis, Alexander Felfernig, et al. "Report on the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023) at ACM RecSys 2023." ACM SIGIR Forum 57, no. 2 (2023): 1–6. http://dx.doi.org/10.1145/3642979.3642999.

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The 10th edition of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems was held as part of the 17th ACM Conference on Recommender Systems (RecSys), the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. The workshop was organized as a hybrid event: the physical session took place on September 18th at the venue of the main conference, Singapore, with the possibility for authors to present remotely. The IntRS workshop brings together an interdisciplinary community of researche

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Ninamango Bazán, Carlos Eduardo, Carlos Alejandro De León Ríos, Rainer Fernández Rabanal, Maricielo Corazon Vasquez Navarro, Xiomara Veronica Vega Rivera, and Pedro Leonardo Tito Huamani. "Contexto de la Pandemia COVID-19 y la Nueva Realidad Empresarial." Revista de Ciencias Sociales y Sostenibilidad 2, no. 1 (2022): 1–15. http://dx.doi.org/10.56111/recsys.2022.v2.n1.p1-15.

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La pandemia de la COVID-19 representa un gran desafío para el sector empresarial, dado que provocó cambios de gran magnitud en diferentes industrias. Por este motivo, el objetivo del presente trabajo es presentar los efectos de la pandemia de la COVID-19 en el mundo empresarial. Para esto, se recurrió a una metodología bibliométrica, la cual consistió en la revisión de artículos científicos en la base de datos Scopus. La búsqueda y selección de fuentes indicó que el contexto actual ocasionó tanto impactos positivos como negativos en el mundo empresarial. Los resultados desprendidos hacen refer

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Vásquez Bernal, Oscar Alejandro, William Eduardo Mosquera Laverde, and Camilo Mauricio Grillo Torres. "Enfoque de sistemas integrados de gestión en desempeño de organizaciones para toma de decisiones." Revista de Ciencias Sociales y Sostenibilidad 2, no. 1 (2022): 17–27. http://dx.doi.org/10.56111/recsys.2022.v2.n1.p17-27.

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En este artículo se mostró la importancia de la toma de decisiones enmarcadas en el desarrollo de los sistemas de gestión en las pequeñas y medianas empresas (PYMES), debido a que la adopción de los sistemas de gestión ha crecido en importancia estratégica dentro de las organizaciones; para algunas dieron respuesta al cumplimiento de las reglamentaciones ynormatividad de algún ente de control, para otras, un efecto de diferentes aspectos que afectaron el entorno competitivo.Se observó un incremento en la importancia en las PYMES cuyas actividades productivas y de servicios aportaron un porcent

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Morales Cauti, Guisseppi Paul, Linda Jessie Palomino Gonzales, Ximena Massiel Paz Arrieta, and Martha Sofia Zúñiga Rodríguez. "Causas de la denegatoria del licenciamiento en universidades privadas de Lima y su impacto en el desarrollo nacional." Revista de Ciencias Sociales y Sostenibilidad 2, no. 1 (2022): 39–49. http://dx.doi.org/10.56111/recsys/2022.v2.n1.p39-49.

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Resolver el problema del servicio educativo universitario en el Perú no es un proyecto sencillo; pero con la vigencia de la Ley Universitaria y el diagnóstico realizado en marco del proceso de licenciamiento, se ha iniciado un proceso que debe conduce a mejoras progresivas de este servicio público; por ello, la presente investigación tuvo como objetivo analizar el proceso delicenciamiento de las universidades de Lima y las causales de denegatoria en el marco del cumplimiento de las condiciones básicas de calidad, desde la perspectiva del beneficio en el interés del estudiante y su impacto en e

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Felipe-Bravo, Gaby Mónica, Paula Jimena Castro-García, and Nicola Giuseppe Torres-Quiroz. "Prácticas medioambientales en el sector hotelero peruano." Revista de Ciencias Sociales y Sostenibilidad 2, no. 1 (2022): 28–38. http://dx.doi.org/10.56111/recsys/2022.v2.n1.p28-38.

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A nivel mundial son muchos los esfuerzos que se están realizando para minimizar el daño al medio ambiente, el sector turístico no es la excepción, las acciones inician con el reclutamiento de los colaboradores, hasta las actividades proyectadas en las cuales participará el cliente. La investigación tuvo como objetivo evaluar el nivel de cumplimiento de las prácticas medioambientales en un hotel 4 estrellas en la ciudad de Trujillo, en el Perú, año 2021. El tipo de estudio fue cuantitativo, aplicado, descriptivo y transversal. La población se centró en 3 establecimientos hoteleros categorizados

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Nomberto Luperdi, Ana Zoila, Mario Edison Ninaquispe Soto, Bruno Padilla Torres, Helen Carolina Adauto Celis, and Luz Andrea Toribio Alomia. "Beneficios ambientales, nutricionales y económicos de la entomofagia en países hispanohablantes en los últimos 15 años: una revisión sistemática de literatura." Revista de Ciencias Sociales y Sostenibilidad 2, no. 1 (2022): 50–65. http://dx.doi.org/10.56111/recsys/2022.v2.n1.p50-65.

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La Revisión Sistemática de Literatura Científica, lleva por título “Beneficios medioambientales, nutricionales y económicos de la entomofagia en países hispanohablantes en los últimos 15 años” se desarrolló proyectando que a futuro esta práctica puede ser una solución sostenible a problemáticas como la contaminación excesiva por parte de la industria ganadera, el alto coste que supone la alimentación del ganado y la inseguridad alimentaria. El objetivo planteado fue establecer cuáles son los resultados más importantes, de los estudios teóricos y empíricos, acerca de los beneficios medioambient

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Zhao, Xiangyu. "Adaptive and automated deep recommender systems." ACM SIGWEB Newsletter, Spring (April 2022): 1–4. http://dx.doi.org/10.1145/3533274.3533277.

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Dr. Xiangyu Zhao is an assistant professor of the school of data science at City University of Hong Kong (CityU). Prior to CityU, he completed his PhD (2021) at MSU under the advisory of Dr. Jiliang Tang, MS (2017) at USTC and BEng (2014) at UESTC. His current research interests include data mining and machine learning, especially (1) Personalization, Recommender System, Online Advertising, Search Engine, and Information Retrieval; (2) Urban Computing, Smart City, and GeoAI; (3) Deep Reinforcement Learning, AutoML, and Multimodal ML; and (4) AI for Social Computing, Finance, Education, Ecosyst

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Erens, Pamela. "Recess." Chicago Review 43, no. 1 (1997): 77. http://dx.doi.org/10.2307/25304142.

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Hawkins, Sheryl T. "Recess." Callaloo 14, no. 2 (1991): 549. http://dx.doi.org/10.2307/2931660.

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Franklin, Robert. "Recess." Prairie Schooner 93, no. 2 (2019): 108. http://dx.doi.org/10.1353/psg.2019.0082.

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Eggert, Susanne, Jan Keilhauer, and Elke Stolzenburg. "Vernetzung von rechts und gegen rechts." merz | medien + erziehung 55, no. 5 (2011): 8–9. http://dx.doi.org/10.21240/merz/2011.5.8.

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Rechte Einstellungen sind ein stabiler Bestandteil westlicher Gesellschaften. Das Phänomen wird vertreten durch die bekannten Rechtsaußen-Parteien, über eine durchaus vielschichtige und schwer durchschaubare rechte Szene, die mal neonazistisch, mal antiislamisch, antisemitisch, nationalistisch oder antidemokratisch daher kommt, bis hin zu Formen rechter Jugendkulturen, die heute äußerlich nur noch schwer von nicht-rechten Jugendkulturen zu unterscheiden sind. Die Problematik lässt sich aber nicht auf bekennende Rechte oder sogenannte Rechtsextreme reduzieren. In einer breiteren Öffentlichkeit

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Ousselin, E. "Recits marquisiens: recits traditionnels des iles Marquises." French Studies 68, no. 3 (2014): 435–36. http://dx.doi.org/10.1093/fs/knu118.

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Coolkens, Rosalie, Phillip Ward, Jan Seghers, and Peter Iserbyt. "The Effect of Organized Versus Supervised Recess on Elementary School Children’s Participation, Physical Activity, Play, and Social Behavior: A Cluster Randomized Controlled Trial." Journal of Physical Activity and Health 15, no. 10 (2018): 747–54. http://dx.doi.org/10.1123/jpah.2017-0591.

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Background: Recess strategies that increase children’s physical activity and contribute to the daily 60 minutes of moderate to vigorous physical activity (MVPA) are recommended. Methods: A cluster randomized trial was conducted to examine the effect of supervised versus organized recess on children’s participation, physical activity, play, and social behavior. In supervised recess, children were free to play, and physical education (PE) teachers ensured safety. In organized recess, PE teachers provided challenging tasks. Data were collected using systematic observation. Children (N = 281; 8–10

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Yin, Xueke. "How Effective are Recasts in Providing Corrective Feedback? - An Analysis of Recent Perspectives." International Journal of Applied Linguistics and English Literature 10, no. 1 (2021): 33. http://dx.doi.org/10.7575/aiac.ijalel.v.10n.1p.33.

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Inspired by the previous recast literature, this paper aims to investigate whether more explicit recasts are more effective than implicit recasts in second language grammar teaching and learning. Four empirical studies (two classroom-based and two laboratory-based) on implicit and explicit recasts were reviewed. In the two classroom-based studies, recasts were coded as explicit or implicit according to their length, intonation, number of changes, type of change, prosodic emphasis, etc. The effectiveness of recasts was measured by learners’ successful uptake rate and test scores. Conclusion dra

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London, Rebecca A. "The right to play: Eliminating the opportunity gap in elementary school recess." Phi Delta Kappan 101, no. 3 (2019): 48–52. http://dx.doi.org/10.1177/0031721719885921.

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It is well documented that recess helps elementary schoolchildren learn and develop socially, emotionally, and physically. Rather than simply a break from class, recess offers benefits with the potential to enhance student learning. Yet many children, especially those in low-income and Black and Latinx communities, do not have the same access to recess at as their more affluent, White counterparts. Rebecca London calls for a closing of the recess opportunity gap by ensuring access to daily recess for all children at school, ceasing the practice of withholding recess and as punishment, and desi

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Shao, Jun-peng, Guang-dong Liu, Xiao-dong Yu, Yan-qin Zhang, Xiu-li Meng, and Hui Jiang. "Effect of recess depth on lubrication performance of annular recess hydrostatic thrust bearing by constant rate flow." Industrial Lubrication and Tribology 70, no. 1 (2018): 68–75. http://dx.doi.org/10.1108/ilt-03-2017-0066.

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Purpose The purpose of this paper is to describe a simulation and experimental research concerning the effect of recess depth on the lubrication performance of a hydrostatic thrust bearing by constant rate flow. Design/methodology/approach The computational fluid dynamics and finite volume method have been used to compute the lubrication characteristics of an annular recess hydrostatic thrust bearing with different recess depths. The performances are oil recess pressure, oil recess temperature and oil film velocity. The recess depth has been optimized. A test rig is established for testing the

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Staňková, Eliška. "Syphilis congenita recens - case reports." Dermatologie pro praxi 11, no. 3 (2017): 148–50. http://dx.doi.org/10.36290/der.2017.029.

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Pellegrini, A. D., and Peter K. Smith. "School Recess: Implications for Education and Development." Review of Educational Research 63, no. 1 (1993): 51–67. http://dx.doi.org/10.3102/00346543063001051.

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In this article the empirical research on the role of school recess is reviewed. Recess is first defined, and then the effects of child-level variables (e.g., gender, age, and temperament) and school-level variables (e.g., recess timing and duration) on children’s recess behavior are reviewed. The implications of recess are discussed in terms of impact on classroom behavior and on measures of social and cognitive competence. It is concluded that recess has important educational and developmental implications. Further research in this area is urgently needed, and some promising areas of inquiry

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Lai, Chun, Fei Fei, and Robin Roots. "Contingency of Recasts and Noticing." CALICO Journal 26, no. 1 (2013): 70–90. http://dx.doi.org/10.1558/cj.v26i1.70-90.

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Recasts are an important type of implicit negative feedback that has attracted much attention in both L1 research and SLA research. The utility of recasts in face-to-face interaction has been empirically established, and the contingency of recasts is argued to be the key. However, the efficacy of recasts in computer-mediated communication (CMC), text-based online chatting in particular, remains questionable due to the possible violation of this contingency factor in the "split negotiation routines" commonly observed in CMC discourse. This study used a repeated-measure design to examine the pot

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Wacha, Richard Charles, and Yeu-Ting Liu. "Testing the efficacy of two new variants of recasts with standard recasts in communicative conversational settings: An exploratory longitudinal study." Language Teaching Research 21, no. 2 (2016): 189–216. http://dx.doi.org/10.1177/1362168815624268.

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The purpose of this exploratory longitudinal study was to evaluate the efficacy of two new forms of recasts (i.e. elaborated and paraphrased recasts), each of which was designed to be more in accordance with contested views of input processing. The effectiveness of the two new forms of recasts was compared to that of conventional standard recasts. To this end, an experienced language teacher engaged four intermediate-level learners of English as a foreign language (EFL) in weekly, one-on-one, English conversation sessions under four instructional conditions (elaborated recast, paraphrased reca

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Wang, Lei, and Shuyun Jiang. "Performance Analysis of High-Speed Deep/Shallow Recessed Hybrid Bearing." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/918767.

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The present paper proposes a theoretical analysis of the performance of deep/shallow recessed hybrid bearing. It is intended that, on the basis of the numerical results drawn from this study, appropriate shallow recess depth and width can be determined for use in the bearing design process. By adopting bulk flow theory, the turbulent Reynolds equation and energy equation are modified and solved numerically including concentrated inertia effects at the recess edge with different depth and width of shallow recess. The results indicate that the load capacity, drag torque increases as the depth of

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Wu, Wei-Ting, Ke-Vin Chang, Ondřej Naňka, et al. "Ultrasound Imaging of the Articularis Genus Muscle: Implications for Ultrasound-Guided Suprapatellar Recess Injection." Diagnostics 14, no. 2 (2024): 183. http://dx.doi.org/10.3390/diagnostics14020183.

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Elucidating its dynamic interaction within the knee joint, this exploration delves into the awareness regarding the articularis genus muscle for ultrasound-guided suprapatellar recess injections. While injections into the infrapatellar recess may proceed without ultrasound guidance, we highlight concerns regarding the potential cartilage injury. In contrast, especially with ultrasound guidance, suprapatellar recess injections significantly mitigate this risk, especially in the case of collapsed recess. Originating from the distal femur and vastus intermedius, the articularis genus muscle influ

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