Ontological User Profiling on Personalized Recommendation in e-Commerce

He, Siping; Fang, Meiqi

doi:10.1109/icebe.2008.26

Cited by 6 publications

(1 citation statement)

References 5 publications

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“…Jayakumar and Shobana [26] followed the potential of user profiles in searching web information and established a user profile ontology based on basic information and professional experience. He and Fang [27] explored an ontological method of depicting user profiles based on browsing history and provided personalized information services in ecommerce with long-term and short-term interests. In addition, user profiles play significant roles in social networks, especially in relationship analysis and friend recommendation [28] .…”

Section: User Profile Modelingmentioning

confidence: 99%

Survey and Tutorial on Hybrid Human-Artificial Intelligence

Shi

Zhou

Liu

et al. 2023

Tsinghua Sci. Technol.

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The growing computing power, easy acquisition of large-scale data, and constantly improved algorithms have led to a new wave of artificial intelligence (AI) applications, which change the ways we live, manufacture, and do business. Along with this development, a rising concern is the relationship between AI and human intelligence, namely, whether AI systems may one day overtake, manipulate, or replace humans. In this paper, we introduce a novel concept named hybrid human-artificial intelligence (H-AI), which fuses human abilities and AI capabilities into a unified entity. It presents a challenging yet promising research direction that prompts secure and trusted AI innovations while keeping humans in the loop for effective control. We scientifically define the concept of H-AI and propose an evolution road map for the development of AI toward H-AI. We then examine the key underpinning techniques of H-AI, such as user profile modeling, cognitive computing, and human-in-the-loop machine learning. Afterward, we discuss H-AI's potential applications in the area of smart homes, intelligent medicine, smart transportation, and smart manufacturing. Finally, we conduct a critical analysis of current challenges and open gaps in H-AI, upon which we elaborate on future research issues and directions.

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Section: User Profile Modelingmentioning

confidence: 99%