E-learning recommender system dataset by Mounir Hafsa, Pamela Wattebled, Julie Jacques, Laetitia Jourdan

Subjects: “…Recommender systems…”
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Recommender system for Real Estate Management by Tomas Ginevičius, Artūras Kaklauskas, Paulius Kazokaitis, Jurgita Alchimovienė

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Opinion based intelligent recommender system by Yuen, Jing Wen

“…This project can be extrapolated to real-life applications, such as e- commerce recommender systems, by recommending products to users based on their social media content.…”
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Opinion-based intelligent recommender system by Poh, Ying Xuan

“…In this paper, we proposed to design an opinion-based intelligent recommender system utilising deep learning. This system incorporates aspect-based sentiment analysis to understand and quantify text, followed by performing collaborative filtering techniques to build a recommender system. …”
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Recommender system to ensure academic success by M Heriz Putra Yusoff

“…Recommender system has been utilised as a tool to predict and suggest relevant items to users. …”
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Evaluating algorithms for an expertise recommender system by Uma Manikantan

“…This study evaluates two algorithms, Support Vector Machine and Bayesian Logistic Regression as applied to an Expertise Recommender System, and compares the results. The expertise area examined is academic research, the information being extracted from faculty web pages of universities world-wide. …”
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Interactive recommender system for images and video by Muhammad Ghalib Mohamed

“…Recommending items or products to users that they may not have seen or acted upon. A recommender system employs collaborative filtering techniques to predict a user’s liking for a certain item. …”
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Recommender system based on semantic similarity by Karamollah, Bagheri Fard, Nilashi, Mehrbakhsh, Rahmani, Mohsen, Ibrahim, Othman

“…For the same reason the recommendation systems are designed to help finding information in large websites. …”

Recommender Systems and Collaborative Filtering by Fernando Ortega, Ángel González-Prieto

“…Recommender Systems (RSs) have become an essential tool for the information society [...]…”
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The Definition of Novelty in Recommendation System by Liang Zhang

“…User satisfaction with recommender systems is related not only to how accurately the system recommends but also to how much it supports the user’s decision making. …”
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A survey of recommendation systems by Wanzhen ZHOU, Di CAO, Yunfeng XU, Bin LIU

Subjects: “…computer neural network; recommendation system; data mining; deep learning; information overload…”
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Towards Cognitive Recommender Systems by Amin Beheshti, Shahpar Yakhchi, Salman Mousaeirad, Seyed Mohssen Ghafari, Srinivasa Reddy Goluguri, Mohammad Amin Edrisi

Subjects: “…recommender systems…”
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Avoiding congestion in recommender systems by Xiaolong Ren, Linyuan Lü, Runran Liu, Jianlin Zhang

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Recommendation System Using Autoencoders by Diana Ferreira, Sofia Silva, António Abelha, José Machado

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Controlling privacy in recommender systems by Xin, Yu, Jaakkola, Tommi S.

“…Recommender systems involve an inherent trade-off between accuracy of recommendations and the extent to which users are willing to release information about their preferences. …”
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Towards Visualization Recommendation Systems by Vartak, Manasi, Huang, Silu, Siddiqui, Tarique, Madden, Samuel R, Parameswaran, Aditya

“…We detail the key requirements and design considerations for a visualization recommendation system. We also identify a number of challenges in realizing this vision and describe some approaches to address them.…”
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Adaptive music recommendation system by Yang, Fan, M. Eng. Massachusetts Institute of Technology

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The Audiomomma Music Recommendation System by Alvira, Mariano, Paris, Jim, Rifkin, Ryan

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Data analysis for recommender systems by Bai, Yuxin

“…With the growing amount of information online, recommender systems are used widely as a strategic approach to address the issue of information overload. …”
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Representation learning for recommender systems by Lucas, Vinh Tran

“…Recommender systems are widely used in many big companies such as Facebook, Google, Twitter, LinkedIn, Amazon and Netflix. …”
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