Recommender systems - Open Access .click

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Recommendation systems are critical tools used by marketing departments to provide customers with product recommendations. Data scientists also use recommendation system analysis to assess the effectiveness of product and service suggestions. There are two types of recommendation systems: content-based and collaborative filtering.
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Recommender systems

Communications of the ACM, 1997
Paul Resnick, Hal R. Varian
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Recommendation Systems

2018
K. G. Srinivasa, Siddesh G. M., Srinidhi H. +2 more
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Recommender Systems

2020
Jie Lu, Qian Zhang, Guangquan Zhang
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Obesity and adverse breast cancer risk and outcome: Mechanistic insights and strategies for intervention

Ca-A Cancer Journal for Clinicians, 2017
Cynthia Morata-Tarifa, Joyce M Slingerland +1 more
exaly

Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma

Ca-A Cancer Journal for Clinicians, 2020
Aaron J Grossberg, William L Hwang, Anirban Maitra +2 more
exaly

Recommendation Systems

2012
Esther Pacitti, Reza Akbarinia, Manal El-Dick +2 more
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Recommendations Systems

2019
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Oral complications of cancer and cancer therapy

Ca-A Cancer Journal for Clinicians, 2012
Joel B Epstein, Rene-Jean Bensadoun, Andrei Barasch +2 more
exaly

The financial burden and distress of patients with cancer: Understanding and stepping‐up action on the financial toxicity of cancer treatment

Ca-A Cancer Journal for Clinicians, 2018
Pricivel M Carrera +2 more
exaly

recommender system
7. clean energy
deep learning

collaborative filtering
8. economic growth
12. responsible consumption

recommendation systems
3. good health
machine learning