Results 251 to 260 of about 2,553,529 (294)

A graph neural network recommendation algorithm based on multi-scale attention and contrastive learning. [PDF]

Sci Rep
Pu D, Zhang Y, Qian Z, Xie G, Pu D.
europepmc   +1 more source

Skin examination in extreme conditions. [PDF]

Acta Biochim Pol
Igielska-Kalwat J.
europepmc   +1 more source

Improving the Performance of Cold-Start Recommendation by Fusion of Attention Network and Meta-Learning

Electronics, 2023
The cold-start problem has always been a key challenge in the recommendation research field. As a popular method to learn a learner that can rapidly adapt to a new task through a small number of updates, meta-learning is considered to be a feasible ...
Xiaotong Zhang, Cheng Xu, Shilong Liu
exaly   +2 more sources

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Cold-Start Recommendation for On-Demand Cinemas

2020
The on-demand cinemas, which has emerged in recent years, provide offline entertainment venues for individuals and small groups. Because of the limitation of network speed and storage space, it is necessary to recommend movies to cinemas, that is, to suggest cinemas to download the recommended movies in advance.
Beibei Li 0001, Beihong Jin, Taofeng Xue, Kunchi Liu, Qi Zhang, Sihua Tian   +5 more
openaire   +2 more sources

A hybrid approach for cold start recommendations

2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 2017
The work presented in this paper is part of the system developed by our team for RecSys challenge 2017. XING is a social networking website that allows the recruiters to post their job openings. It also allows the interested candidates to look up these job openings and apply for the job if suits their requirements.
Madhulika Agrawal, Teresa Gonçalves 0001, Paulo Quaresma   +2 more
openaire   +3 more sources

On cold start for associative tag recommendation

Journal of the Association for Information Science and Technology, 2015
Tag recommendation strategies that exploit term co‐occurrence patterns with tags previously assigned to the target object have consistently produced state‐of‐the‐art results. However, such techniques work only for objects with previously assigned tags.
Eder Ferreira Martins, Fabiano Muniz Belém, Jussara M. Almeida, Marcos André Gonçalves   +3 more
openaire   +1 more source

Methods and metrics for cold-start recommendations

Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval, 2002
We have developed a method for recommending items that combines content and collaborative data under a single probabilistic framework. We benchmark our algorithm against a naive Bayes classifier on the cold-start problem, where we wish to recommend items that no one in the community has yet rated.
Andrew I. Schein, Alexandrin Popescul, Lyle H. Ungar, David M. Pennock   +3 more
openaire   +1 more source

Collaborative Filtering and Deep Learning Based Recommendation System for Cold Start Items [PDF]

Expert Systems With Applications, 2017
Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users.
Zuoyin Tang, Jianhua He
exaly   +2 more sources