An Innovative Approach: Typicality-Based Collaborative Filtering for Recommender Systems

Talukdar, Veera; Veeraiah, Vivek; Roy, Devika Rani; Pandey, Jay Kumar; Gupta, Ankur; Dhabliya, Dharmesh

doi:10.1109/aece59614.2023.10428576

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2024

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Cited by 2 publications

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Explainable Machine Learning Models for Clinical Decision Support Systems

Kumar,

Veeraiah,

Gongada

et al. 2024

2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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Explainable Machine Learning Models for Clinical Decision Support Systems

Kumar,

Veeraiah,

Gongada

et al. 2024

2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)

View full text Add to dashboard Cite

Driving Sales and Customer Engagement

Deshmukh,

Panchbhai,

Gorkhe

et al. 2024

Advances in Computational Intelligence and Robotics

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This chapter will aim at discussing the function of recommendation systems and its added values in the context of personal marketing communications with special focus on sales promotion in the current society especially when it comes to use of AI in recommendation systems. Starting with the introduction of recommendation systems and the theory it work on, the chapter will proceed to the development of AI in the sphere of marketing and the methods applied to the procedure of individualized marketing. It also looks into several real-life uses spanning different industries and describes essential issues, including ethics and privacy in marketing aided by artificial intelligence. Through intensive literature review and case analysis, the chapter will talk more about successful implementation and other trends likely to happen in future. Different perspectives of this chapter are going to focus on AI Recommendation Systems as one of the most important tools that influence sales, customers' satisfaction and brand loyalty in the future of marketing strategies.

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An Innovative Approach: Typicality-Based Collaborative Filtering for Recommender Systems

Cited by 2 publications

References 21 publications

Explainable Machine Learning Models for Clinical Decision Support Systems

Explainable Machine Learning Models for Clinical Decision Support Systems

Driving Sales and Customer Engagement

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