The Prefiltering Techniques in Emotion Based Place Recommendation Derived by User Reviews by U. A. Piumi Ishanka, Takashi Yukawa

“…Context-aware recommendation systems attempt to address the challenge of identifying products or items that have the greatest chance of meeting user requirements by adapting to current contextual information. …”
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A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features by Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri

“…<italic>Goal:</italic> The purpose of this study is to evaluate the importance of cardiorespiratory variables within a Reinforcement Learning (RL) recommendation system aimed at establishing optimal strategies for drug treatment of septic patients in the intensive care unit (ICU). …”
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Music Personalized Label Clustering and Recommendation Visualization by Yongkang Huo

“…First, this paper describes the main ideas and methods used in current recommendation systems and summarizes the areas that need attention and consideration. …”
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Key Technologies and Discrete Dynamic Modeling Analysis of Online Travel Planning System Based on Big Data Scenario Aware Service by Yange Hao, Na Song

“…The key technology of online travel recommendation system has been widely concerned by many Internet experts. …”
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Hierarchical Learning: A Hybrid of Federated Learning and Personalization Fine-Tuning by Li Shuyi, Zhang Bairong

“…This hybrid approach not only enhances model accuracy but also preserves data privacy and increases scalability, making it a promising solution for decentralized recommendation systems.…”
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Joint embedding–classifier learning for interpretable collaborative filtering by Clémence Réda, Jill-Jênn Vie, Olaf Wolkenhauer

“…Abstract Background Interpretability is a topical question in recommender systems, especially in healthcare applications. …”
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Invariant Representation Learning in Multimedia Recommendation with Modality Alignment and Model Fusion by Xinghang Hu, Haiteng Zhang

“…Multimedia recommendation systems aim to accurately predict user preferences from multimodal data. …”
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An Improved Recommendation Method Based on Content Filtering and Collaborative Filtering by Lei Fu, XiaoMing Ma

“…The emergence and application of the network marketing recommendation system have greatly improved this series of problems. …”
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Exercise Recommendation Model Based on Cognitive Level and Educational Big Data Mining by Yongming Pu, Hongming Chen

“…Compared with other recommendation systems, this model has higher accuracy and recommendation effect.…”
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Sistem Rekomendasi Profesi Berdasarkan Dimensi Big Five Personality Menggunakan Fuzzy Inference System Tsukamoto by Farhanna Mar'i, Wayan Firdaus Mahmudy, Cleoputri Yusainy

“…In a company, a professional recommendation system can be used to place an employee in the right position. …”
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Research on E-Commerce Platform-Based Personalized Recommendation Algorithm by Zhijun Zhang, Gongwen Xu, Pengfei Zhang

“…In the recommendation prediction stage, considering timeliness of the recommendation system, time weighted based recommendation prediction formula is adopted to design a personalized recommendation model by integrating level filling method and rating time. …”
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Personalized Clothing Recommendation Based on User Emotional Analysis by Xueping Su, Meng Gao, Jie Ren, Yunhong Li, Matthias Rätsch

“…However, the recommendation quality of the existing clothing recommendation system is not enough to meet the user’s needs. …”
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Personalized fund recommendation with dynamic utility learning by Jiaxin Wei, Jia Liu

“…Abstract This study introduces a fund recommendation system based on the $$\epsilon$$ ϵ -greedy algorithm and an incremental learning framework. …”
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A Novel Recommendation Algorithm Integrates Resource Allocation and Resource Transfer in Weighted Bipartite Network by Qiang Sun, Leilei Shi, Lu Liu, Zixuan Han, Liang Jiang, Yan Wu, Yeling Zhao

“…Experiments are conducted on the MovieLens training dataset, and the experimental results show that the proposed algorithm outperforms classical collaborative filtering systems and network structure based recommendation systems in terms of recommendation accuracy and hit rate.…”
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A Cloud API Personalized Recommendation Method Based on Multiple Attribute Features and Mashup Requirement Attention by Limin Shen, Yuying Wang, Chengyu Li, Zhen Chen

“…In current mashup-oriented cloud API recommendation systems, insufficient attention to personalized development requirements remains a common issue, particularly regarding developers&#x2019; needs for attributes such as functionality similarity and complementarity. …”
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Design and Implementation of Attention-Based CR System in the Context of Big Data by Zheyi Wang, Yanli Kuang, Xin Lyu

“…The recommendation accuracy of traditional product recommendation systems is insufficient. Therefore, an improved deep factor decomposition machine algorithm combining adaptive regularization and attention mechanisms is proposed, and big data components are integrated to enable the algorithm to support more data input types. …”
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Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm by Jing Li, Zhou Ye

“…In this paper, a personalized online education platform based on a collaborative filtering algorithm is designed by applying the recommendation algorithm in the recommendation system to the online education platform using a cross-platform compatible HTML5 and high-performance framework hybrid programming approach. …”
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New Similarity of Triangular Fuzzy Number and Its Application by Xixiang Zhang, Weimin Ma, Liping Chen

“…Finally, a simulated collaborative filtering recommendation system is developed which uses cloud model and triangular fuzzy number to express users’ comprehensive evaluation on items, and result shows that the accuracy of collaborative filtering recommendation based on triangular fuzzy number is higher.…”
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Evaluation of the Use of Artificial Intelligence in Teaching Learning Evaluation Courses by Muhamad Raffi Fadliansyah, Rian Dwiyanto, Nur Syamsiyah Nur Syamsiyah

“…By utilizing AI technology, such as chatbots, learning recommendation systems, and data analysis tools, teaching this course is expected to increase the effectiveness, efficiency, and engagement of students in the learning process. …”
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Deep Sequential Model for Anchor Recommendation on Live Streaming Platforms by Shuai Zhang, Hongyan Liu, Jun He, Sanpu Han, Xiaoyong Du

“…Therefore, a personalized recommendation system is important for live streaming platforms. …”
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