A Hybrid Recommendation System Based on Human Curiosity

Santos, Alan Menk dos

doi:10.1145/2792838.2796545

Cited by 9 publications

(1 citation statement)

References 5 publications

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“…In addition to the models mentioned earlier, some researchers have attempted to model a user's curiosity explicitly based on questionnaires and surveys [163], but this is beyond the scope of this chapter. Despite the loss of accuracy, curiosity-driven recommender systems can outperform traditional methods in terms of coverage, diversity, and personalization, which are more desirable in real-world applications.…”

Section: Discussionmentioning

confidence: 99%

Curiosity-driven learning in artificial intelligence and its applications

Sun

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I would like to express my heartfelt gratitude to my supervisor, Prof Miao Chunyan, for her invaluable guidance, insightful feedback, and constant encouragement throughout my Ph.D journey. Her vast knowledge, experience, and unwavering support have been instrumental in shaping my research and shaping me into a better researcher. I am also grateful to Dr. Qian Hangwei and Dr. Zeng Zhiwei for their assistance and advice that helped me overcome challenges and obstacles. Furthermore, I am thankful to Alibaba-NTU Singapore Joint Research Institute and the Singapore Economic Development Board (EDB) for their generous support and funding of this research project. Without their assistance, this research would not have been possible. Finally, I would like to express my gratitude to my family and friends for their continuous love, support, and encouragement during this long and challenging journey. Their unwavering belief in me has been a constant source of motivation, and I am grateful to have them in my life.

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Section: Discussionmentioning

confidence: 99%