{"title":"添加ReputationRank会员推广使用天际线运营商在社会网络。","authors":"Jiping Zheng, Siman Zhang","doi":"10.1186/s40649-018-0055-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>To identify potential stars in social networks, the idea of combining member promotion with skyline operator attracts people's attention. Some algorithms have been proposed to deal with this problem so far, such as skyline boundary algorithms in unequal-weighted social networks.</p><p><strong>Methods: </strong>We propose an improved member promotion algorithm by presenting <i>ReputationRank</i> based on eigenvectors as well as <i>Influence</i> and <i>Activeness</i> and introduce the concept of skyline distance. Furthermore, we perform skyline operator over non-skyline set and choose the infra-skyline as our candidate set. The added <i>ReputationRank</i> helps a lot to describe the importance of a member while the skyline distance assists us to obtain the necessary condition for not being dominated so that some meaningless plans can be pruned.</p><p><strong>Results: </strong>Experiments on the DBLP and WikiVote datasets verify the effectiveness and efficiency of our proposed algorithm.</p><p><strong>Conclusions: </strong>Treating the infra-skyline set as candidate set reduces the number of candidates. The pruning strategies based on dominance and promotion cost decrease the searching space.</p>","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"5 1","pages":"7"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40649-018-0055-9","citationCount":"0","resultStr":"{\"title\":\"Adding <i>ReputationRank</i> to member promotion using skyline operator in social networks.\",\"authors\":\"Jiping Zheng, Siman Zhang\",\"doi\":\"10.1186/s40649-018-0055-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>To identify potential stars in social networks, the idea of combining member promotion with skyline operator attracts people's attention. Some algorithms have been proposed to deal with this problem so far, such as skyline boundary algorithms in unequal-weighted social networks.</p><p><strong>Methods: </strong>We propose an improved member promotion algorithm by presenting <i>ReputationRank</i> based on eigenvectors as well as <i>Influence</i> and <i>Activeness</i> and introduce the concept of skyline distance. Furthermore, we perform skyline operator over non-skyline set and choose the infra-skyline as our candidate set. The added <i>ReputationRank</i> helps a lot to describe the importance of a member while the skyline distance assists us to obtain the necessary condition for not being dominated so that some meaningless plans can be pruned.</p><p><strong>Results: </strong>Experiments on the DBLP and WikiVote datasets verify the effectiveness and efficiency of our proposed algorithm.</p><p><strong>Conclusions: </strong>Treating the infra-skyline set as candidate set reduces the number of candidates. The pruning strategies based on dominance and promotion cost decrease the searching space.</p>\",\"PeriodicalId\":52145,\"journal\":{\"name\":\"Computational Social Networks\",\"volume\":\"5 1\",\"pages\":\"7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/s40649-018-0055-9\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Social Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s40649-018-0055-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2018/9/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Social Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40649-018-0055-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/9/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
Adding ReputationRank to member promotion using skyline operator in social networks.
Background: To identify potential stars in social networks, the idea of combining member promotion with skyline operator attracts people's attention. Some algorithms have been proposed to deal with this problem so far, such as skyline boundary algorithms in unequal-weighted social networks.
Methods: We propose an improved member promotion algorithm by presenting ReputationRank based on eigenvectors as well as Influence and Activeness and introduce the concept of skyline distance. Furthermore, we perform skyline operator over non-skyline set and choose the infra-skyline as our candidate set. The added ReputationRank helps a lot to describe the importance of a member while the skyline distance assists us to obtain the necessary condition for not being dominated so that some meaningless plans can be pruned.
Results: Experiments on the DBLP and WikiVote datasets verify the effectiveness and efficiency of our proposed algorithm.
Conclusions: Treating the infra-skyline set as candidate set reduces the number of candidates. The pruning strategies based on dominance and promotion cost decrease the searching space.
期刊介绍：
Computational Social Networks showcases refereed papers dealing with all mathematical, computational and applied aspects of social computing. The objective of this journal is to advance and promote the theoretical foundation, mathematical aspects, and applications of social computing. Submissions are welcome which focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media. Topics include (but are not limited to) the following: -Social network design and architecture -Mathematical modeling and analysis -Real-world complex networks -Information retrieval in social contexts, political analysts -Network structure analysis -Network dynamics optimization -Complex network robustness and vulnerability -Information diffusion models and analysis -Security and privacy -Searching in complex networks -Efficient algorithms -Network behaviors -Trust and reputation -Social Influence -Social Recommendation -Social media analysis -Big data analysis on online social networks This journal publishes rigorously refereed papers dealing with all mathematical, computational and applied aspects of social computing. The journal also includes reviews of appropriate books as special issues on hot topics.
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