Wenguo Yang
Biographic Data
| ID | 10053896 |
|---|---|
| NAME | Wenguo Yang |
| GIVEN NAMES | Wenguo |
| FAMILY NAME | Yang |
| SIGNATURE | YANG W |
| AFFILIATIONS | University of Chinese Academy of Sciences |
| ORCID | 0000-0002-8441-7334 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Supplementary Influence Maximization Problem in Social Networks
Due to important applications in viral marketing, influence maximization (IM) has become a well-studied problem. It aims at finding a small subset of initial users so that they can deliver information to the largest amount of users through the word-of-mouth effect. The original IM only considers a singleton item. And the majority of extensions ignore the relationships among different items or only consider their competitive interactions. In reali…
Team Composition for Competitive Information Spread
Social-media platforms provide citizens a new way to stay informed and offer marketers a shot at promoting their brand. In social advertising, information diversity can create a level playing field for competitive information dissemination. Team diversity is important because teams with a diverse composition tend to perform better over time. The former demands that all the social networks’ users should receive diverse information. The later requi…
Positive Evaluation Maximization in Social Networks
Influence maximization (IM) is a classical and heated issue in online social networks. Although some works have studied multifeature IM, they do not consider this problem from the perspective of users’ preferences. In this article, we construct a novel multifeature spreading model that considers users’ different preferences, namely, the MFP-independent cascade (IC) model, which uses the IC model as the basic propagation model. Some features are p…
Output–Input Ratio Maximization for Online Social Networks
In the last few decades, profit maximization (PM), which is mainly considered for maximizing net profits, i.e., the difference between gain and cost, has been a prominent issue for online social networks (OSNs). However, the output-to-input ratio, which is an important metric in economics, is also worth studying for OSNs. In this article, we present a novel problem that considers the PM problem from the ratio of gain and cost, known as output-to-…
Effector Detection Problem in Social Networks
Nowadays, different innovations spread rapidly in online social networks. An activation state can indicate whether each user adopts the target information. The effector detection problem aims to find a way to generate an activation state as close to an observed one as possible. In this article, based on the influence spread, the unconstrained and constrained effector detection problems are proposed. To tackle them, we design two approximation alg…
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Effector Detection Problem in Social Networks
Nowadays, different innovations spread rapidly in online social networks. An activation state can indicate whether each user adopts the target information. The effector detection problem aims to find a way to generate an activation state as close to an observed one as possible. In this article, based on the influence spread, the unconstrained and constrained effector detection problems are proposed. To tackle them, we design two approximation alg…
Positive Evaluation Maximization in Social Networks
Influence maximization (IM) is a classical and heated issue in online social networks. Although some works have studied multifeature IM, they do not consider this problem from the perspective of users’ preferences. In this article, we construct a novel multifeature spreading model that considers users’ different preferences, namely, the MFP-independent cascade (IC) model, which uses the IC model as the basic propagation model. Some features are p…
Output–Input Ratio Maximization for Online Social Networks
In the last few decades, profit maximization (PM), which is mainly considered for maximizing net profits, i.e., the difference between gain and cost, has been a prominent issue for online social networks (OSNs). However, the output-to-input ratio, which is an important metric in economics, is also worth studying for OSNs. In this article, we present a novel problem that considers the PM problem from the ratio of gain and cost, known as output-to-…
Supplementary Influence Maximization Problem in Social Networks
Due to important applications in viral marketing, influence maximization (IM) has become a well-studied problem. It aims at finding a small subset of initial users so that they can deliver information to the largest amount of users through the word-of-mouth effect. The original IM only considers a singleton item. And the majority of extensions ignore the relationships among different items or only consider their competitive interactions. In reali…
Team Composition for Competitive Information Spread
Social-media platforms provide citizens a new way to stay informed and offer marketers a shot at promoting their brand. In social advertising, information diversity can create a level playing field for competitive information dissemination. Team diversity is important because teams with a diverse composition tend to perform better over time. The former demands that all the social networks’ users should receive diverse information. The later requi…
Mathematical optimization (5 works) · Mathematics (5 works) · Algorithm (4 works) · Computer Science (4 works) · Maximization (4 works) · Approximation algorithm (3 works) · Complex Network Analysis Techniques (3 works) · Submodular set function (3 works) · Mobile Crowdsensing and Crowdsourcing (2 works) · Opinion Dynamics and Social Influence (2 works)