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This paper identifies the factors that have an impact on mobile recommender systems. Recommender systems have become a technology that has been widely used by various online applications in situations where there is an information overload…

Information Retrieval · Computer Science 2018-05-08 Elias Pimenidis , Nikolaos Polatidis , Haralambos Mouratidis

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities…

Physics and Society · Physics 2015-06-04 Linyuan Lü , Matus Medo , Chi Ho Yeung , Yi-Cheng Zhang , Zi-Ke Zhang , Tao Zhou

The recommendation of food items is important for many reasons. Attaining cooking inspiration via digital sources is becoming evermore popular; as are systems, which recommend other types of food, such as meals in restaurants or products in…

Information Retrieval · Computer Science 2017-11-13 Christoph Trattner , David Elsweiler

Everyone eats. However, people do not always know what to eat. They need a little help and inspiration. Consequently, a number of apps, services, and programs have developed recommenders around food. These cover food, meal, recipe, and…

Information Retrieval · Computer Science 2018-09-18 Carl Anderson

Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on…

Information Retrieval · Computer Science 2017-02-22 Fei Yu , An Zeng , Sebastien Gillard , Matus Medo

The use of mobile devices in combination with the rapid growth of the internet has generated an information overload problem. Recommender systems is a necessity to decide which of the data are relevant to the user. However in mobile devices…

Information Retrieval · Computer Science 2014-09-01 Nikolaos Polatidis , Christos K. Georgiadis

E-commerce recommender systems are becoming increasingly important in the current digital world. They are used to personalize user experience, help customers find what they need quickly and efficiently, and increase revenue for the…

Information Retrieval · Computer Science 2022-12-29 Tanmayee Salunke , Unnati Nichite

In this big data era, it is hard for the current generation to find the right data from the huge amount of data contained within online platforms. In such a situation, there is a need for an information filtering system that might help them…

Recommender systems have fulfilled an important role in everyday life. Recommendations such as news by Google, videos by Netflix, goods by e-commerce providers, etc. have heavily changed everyones lifestyle. Health domains contain similar…

Information Retrieval · Computer Science 2020-07-28 Jia Su , Yi Guan , Yuge Li , Weile Chen , He Lv , Yageng Yan

Personalized recommendations have become a common feature of modern online services, including most major e-commerce sites, media platforms and social networks. Today, due to their high practical relevance, research in the area of…

Information Retrieval · Computer Science 2023-02-07 Pablo Castells , Dietmar Jannach

Recommender systems have been widely applied in different real-life scenarios to help us find useful information. In particular, Reinforcement Learning (RL) based recommender systems have become an emerging research topic in recent years,…

Information Retrieval · Computer Science 2023-06-13 Yuanguo Lin , Yong Liu , Fan Lin , Lixin Zou , Pengcheng Wu , Wenhua Zeng , Huanhuan Chen , Chunyan Miao

Recommender systems have been successfully applied to assist decision making by producing a list of item recommendations tailored to user preferences. Traditional recommender systems only focus on optimizing the utility of the end users who…

Information Retrieval · Computer Science 2017-07-28 Yong Zheng

Recommender systems can be characterized as software solutions that provide users convenient access to relevant content. Traditionally, recommender systems research predominantly focuses on developing machine learning algorithms that aim to…

Information Retrieval · Computer Science 2022-10-20 Dietmar Jannach

Soon after the invention of the Internet, the recommender system emerged and related technologies have been extensively studied and applied by both academia and industry. Currently, recommender system has become one of the most successful…

Information Retrieval · Computer Science 2022-09-07 Zhenhua Dong , Zhe Wang , Jun Xu , Ruiming Tang , Jirong Wen

The number of Internet users had grown rapidly enticing companies and cooperations to make full use of recommendation infrastructures. Consequently, online advertisement companies emerged to aid us in the presence of numerous items and…

Information Retrieval · Computer Science 2018-11-30 S. M. Mahdi Seyednezhad , Kailey Nobuko Cozart , John Anthony Bowllan , Anthony O. Smith

Recommender systems are an essential tool to relieve the information overload challenge and play an important role in people's daily lives. Since recommendations involve allocations of social resources (e.g., job recommendation), an…

Information Retrieval · Computer Science 2022-07-12 Yifan Wang , Weizhi Ma , Min Zhang , Yiqun Liu , Shaoping Ma

With the ever-growing volume of online information, recommender systems have been an effective strategy to overcome such information overload. The utility of recommender systems cannot be overstated, given its widespread adoption in many…

Information Retrieval · Computer Science 2019-07-11 Shuai Zhang , Lina Yao , Aixin Sun , Yi Tay

As recommender systems increasingly guide physical actions, often through wearables and coaching tools, new challenges arise around how users interpret, trust, and respond to this advice. This paper introduces a conceptual framework for…

Human-Computer Interaction · Computer Science 2025-12-22 Alan Said

Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption…

Information Retrieval · Computer Science 2024-11-13 Xin Zhou , Lei Zhang , Honglei Zhang , Yixin Zhang , Xiaoxiong Zhang , Jie Zhang , Zhiqi Shen

Recommender systems play a pivotal role in helping users navigate an overwhelming selection of products and services. On online platforms, users have the opportunity to share feedback in various modes, including numerical ratings, textual…

Information Retrieval · Computer Science 2025-05-27 Emrul Hasan , Mizanur Rahman , Chen Ding , Jimmy Xiangji Huang , Shaina Raza
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