9 results on '"Li, Yingshu"'
Search Results
2. Computing an effective decision making group of a society using social network analysis
- Author
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Kim, Donghyun, Li, Deying, Asgari, Omid, Li, Yingshu, Tokuta, Alade O., and Oh, Heekuck
- Published
- 2014
- Full Text
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3. Neighborhood-based uncertainty generation in social networks
- Author
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Han, Meng, Yan, Mingyuan, Li, Jinbao, Ji, Shouling, and Li, Yingshu
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- 2014
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4. Online sharing of physical activity: does it accelerate the impact of a health promotion program?
- Author
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Manzoor, A., Mollee, J.S., Fernandes de Mello Araujo, E., Klein, M.C.A., van Halteren, A.T., Cai, Zhipeng, Angryk, Rafal, Song, Wenzhan, Li, Yingshu, Cao, Xiaojun, Bourgeois, Anu, Luo, Guangchun, Cheng, Liang, Krishnamachari, Bhaskar, Cai, Zhipeng, Angryk, Rafal, Song, Wenzhan, Li, Yingshu, Cao, Xiaojun, Bourgeois, Anu, Luo, Guangchun, Cheng , Liang, Krishnamachari, Bhaskar, Artificial intelligence, Social AI, and Network Institute
- Subjects
Activity level ,030505 public health ,Knowledge management ,Computer science ,business.industry ,media_common.quotation_subject ,Physical activity ,Data analysis ,02 engineering and technology ,Social networks ,03 medical and health sciences ,Social influence ,Promotion (rank) ,Health promotion ,Physical activity promotion ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Health behavior ,0305 other medical science ,business ,Simulation ,media_common - Abstract
Influence on health behavior from peers is well known and it has been shown that participants in an online physical activity promotion program are generally more successful when they share their achievements through an online community. However, more detailed insights are needed into the mechanisms that explain the influence of a community on physical activity level (PAL). This paper discusses a detailed analysis of a data set of participants in an online physical activity promotion program. The analysis focuses on the comparison two groups of participants, namely participants who will join a community at some point in time and participants who will never join a community. A well-balanced selection is made to eliminate to a large extent factors that dilute the effect of the willingness to partake in a community. We create statistical models that describe the PAL increase at the end of the program. A comparison of these models shows that participants that will participate in a community not only have a higher PAL at the start of the program, but also that the PAL increase is significantly greater compared to participants that will not members. The results further support the hypothesis that the possibility to share achievements is an important feature of successful health promotion programs. At the same time, it raises the question whether part of the success is caused by a selection bias, as people that are willing to participate in a community are already more active at the start.
- Published
- 2016
5. Privacy-Enhancing Preferential LBS Query for Mobile Social Network Users.
- Author
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Siddula, Madhuri, Li, Yingshu, Cheng, Xiuzhen, Tian, Zhi, and Cai, Zhipeng
- Subjects
ONLINE social networks ,SOCIAL networks ,RECOMMENDER systems ,LOCATION-based services - Abstract
While social networking sites gain massive popularity for their friendship networks, user privacy issues arise due to the incorporation of location-based services (LBS) into the system. Preferential LBS takes a user's social profile along with their location to generate personalized recommender systems. With the availability of the user's profile and location history, we often reveal sensitive information to unwanted parties. Hence, providing location privacy to such preferential LBS requests has become crucial. However, the current technologies focus on anonymizing the location through granularity generalization. Such systems, although provides the required privacy, come at the cost of losing accurate recommendations. Hence, in this paper, we propose a novel location privacy-preserving mechanism that provides location privacy through k -anonymity and provides the most accurate results. Experimental results that focus on mobile users and context-aware LBS requests prove that the proposed method performs superior to the existing methods. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
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6. INFLUENCE ANALYSIS: A SURVEY OF THE STATE-OF-THE-ART.
- Author
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Han, Meng and Li, Yingshu
- Subjects
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SOCIAL networks , *SOCIAL network theory , *SOCIAL groups , *WIRELESS sensor networks , *SOCIAL psychology - Abstract
Online social networks have seen an exponential growth in number of users and activities recently. The rapid proliferation of online social networks provides rich data and infinite possibilities for us to analyze and understand the complex inherent mechanism which governs the evolution of the new online world. This paper summarizes the state-of-art research results on social influence analysis in a broad sense. First, we review the development process of influence analysis in social networks based on several basic conceptions and features in a social aspect. Then the online social networks are discussed. After describing the classical models which simulate the influence spreading progress, we give a bird's eye view of the up-to-date literatures on influence diffusion models and influence maximization approaches. Third, we present the applications including web services, marketing, and advertisement services which based on the influence analysis. At last, we point out the research challenges and opportunities in this area for both industry and academia reference. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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7. Efficient respondents selection for biased survey using homophily-high social relation graph.
- Author
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Kim, Donghyun, Zhong, Jiaofei, Lee, Minhyuk, Li, Deying, Li, Yingshu, and Tokuta, Alade O.
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ONLINE social networks ,INTERPERSONAL relations ,INTERNET friendship ,SOCIAL networks ,APPROXIMATION algorithms - Abstract
Online social relationships which can be extracted from various online resources such as online social networks are getting much attention from the research communities since they are rich resources to learn about the members of our society as well as the relationships among them. With the advances of Internet related technologies, online surveys are established as an essential tool for a wide range of applications. One significant issue of online survey is how to select a quality respondent group so that the survey result is reliable. This paper studies the use of pairwise online social relationships among the members of a society to form a biased survey respondent group, which might be useful for various applications. We first introduce a way to construct a homophily-high social relation graph. Then, we introduce the minimum inverse k-core dominating set problem (MIkCDSP), which aims to compute a biased respondent group using the homophily-high social relation graph. We show the problem is NP-hard and most importantly propose a greedy approximation for it. Our simulation based on a real social network shows the proposed algorithm is very effective. [ABSTRACT FROM AUTHOR]
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- 2016
- Full Text
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8. An energy efficient privacy-preserving content sharing scheme in mobile social networks.
- Author
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He, Zaobo, Cai, Zhipeng, Han, Qilong, Tong, Weitian, Sun, Limin, and Li, Yingshu
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INFORMATION sharing ,SOCIAL networks ,DATA encryption ,DATA security ,INFORMATION theory - Abstract
The rising popularity of mobile social media enables personalization of various content sharing and subscribing services. These two types of services entail serious privacy concerns not only to the confidentiality of shared content, but also to the privacy of end users such as their identities, interests and social relationships. Previous works established on the attribute-based encryption (ABE) can provide fine-grained access control of content. However, practical privacy-preserving content sharing in mobile social networks either incurs great risk of information leaking to unauthorized third parties or suffers from high energy consumption for decrypting privacy-preserving content. Motivated by these issues, this paper proposes a publish-subscribe system with secure proxy decryption (PSSPD) in mobile social networks. First, an effective self-contained privacy-preserving access control method is introduced to protect the confidentiality of the content and the credentials of users. This method is based on ciphertext-policy ABE and public-key encryption with keyword search. After that, a secure proxy decryption mechanism is proposed to reduce the heavy burdens of energy consumption on performing ciphertext decryption at end users. The experimental results demonstrate the efficiency and privacy preservation effectiveness of PSSPD. [ABSTRACT FROM AUTHOR]
- Published
- 2016
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9. Task Allocation Model Based on Worker Friend Relationship for Mobile Crowdsourcing.
- Author
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Zhao, Bingxu, Wang, Yingjie, Li, Yingshu, Gao, Yang, and Tong, Xiangrong
- Subjects
ONLINE social networks ,CROWDSOURCING ,CODING theory ,DATA privacy ,COMPUTER algorithms - Abstract
With the rapid development of mobile devices, mobile crowdsourcing has become an important research focus. According to the task allocation, scholars have proposed many methods. However, few works discuss combining social networks and mobile crowdsourcing. To maximize the utilities of mobile crowdsourcing system, this paper proposes a task allocation model considering the attributes of social networks for mobile crowdsourcing system. Starting from the homogeneity of human beings, the relationship between friends in social networks is applied to mobile crowdsourcing system. A task allocation algorithm based on the friend relationships is proposed. The GeoHash coding mechanism is adopted in the process of calculating the strength of worker relationship, which effectively protects the location privacy of workers. Utilizing synthetic dataset and the real-world Yelp dataset, the performance of the proposed task allocation model was evaluated. Through comparison experiments, the effectiveness and applicability of the proposed allocation mechanism were verified. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
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