TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Product Adoption Maximization Leveraging Social Influence and User Interest Mining |
| 영문제목(English Title) |
Product Adoption Maximization Leveraging Social Influence and User Interest Mining |
| 저자(Author) |
Ping Ji
Hui Huang
Xueliang Liu
Xueyou Hu
|
| 원문수록처(Citation) |
VOL 15 NO. 06 PP. 2069 ~ 2085 (2021. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
A Social Networking Service (SNS) platform provides digital footprints to discover users’ interests and track the social diffusion of product adoptions. How to identify a small set of seed users in a SNS who is potential to adopt a new promoting product with high probability, is a key question in social networks. Existing works approached this as a social influence maximization problem. However, these approaches relied heavily on text information for topic modeling and neglected the impact of seed users’ relation in the model. To this end, in this paper, we first develop a general product adoption function integrating both users’ interest and social influence, where the user interest model relies on historical user behavior and the seed users’ evaluations without any text information. Accordingly, we formulate a product adoption maximization problem and prove NP-hardness of this problem. We then design an efficient algorithm to solve this problem. We further devise a method to automatically learn the parameter in the proposed adoption function from users’ past behaviors. Finally, experimental results show the soundness of our proposed adoption decision function and the effectiveness of the proposed seed selection method for product adoption maximization. |
| 키워드(Keyword) |
Product Adoption Maximization
Social networking Service
Influential users
Users’ behaviors
Social Influence Modeling
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| 파일첨부 |
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