Influence maximisation in social networks: A target-oriented estimation
DC Field | Value | Language |
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dc.contributor.author | Ko, Yun-Yong | - |
dc.contributor.author | Chae, Dong-Kyu | - |
dc.contributor.author | Kim, Sang-Wook | - |
dc.date.accessioned | 2022-07-11T05:22:06Z | - |
dc.date.available | 2022-07-11T05:22:06Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2018-10 | - |
dc.identifier.issn | 0165-5515 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/149229 | - |
dc.description.abstract | Influence maximisation (IM) is the problem of finding a set of k-seed nodes that could maximize the amount of influence spread in a social network. In this article, we point out that the existing methods are taking the source-oriented estimation (SOE), which is the main reason of their failure in accurately estimating the amount of potential influence spread of an individual node. We propose a novel target-oriented estimation (TOE) that understands information diffusion more accurately as well as remedies the drawback of the existing methods. Our extensive experiments on four real-world datasets demonstrate that our proposed method outperforms the existing methods consistently with respect to the quality of the selected seed set. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SAGE PUBLICATIONS LTD | - |
dc.title | Influence maximisation in social networks: A target-oriented estimation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chae, Dong-Kyu | - |
dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
dc.identifier.doi | 10.1177/0165551517748289 | - |
dc.identifier.scopusid | 2-s2.0-85042125040 | - |
dc.identifier.wosid | 000444425600008 | - |
dc.identifier.bibliographicCitation | JOURNAL OF INFORMATION SCIENCE, v.44, no.5, pp.671 - 682 | - |
dc.relation.isPartOf | JOURNAL OF INFORMATION SCIENCE | - |
dc.citation.title | JOURNAL OF INFORMATION SCIENCE | - |
dc.citation.volume | 44 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 671 | - |
dc.citation.endPage | 682 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Information Science & Library Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Information Science & Library Science | - |
dc.subject.keywordPlus | COMMUNITY STRUCTURE | - |
dc.subject.keywordAuthor | Influence maximisation | - |
dc.subject.keywordAuthor | information diffusion | - |
dc.subject.keywordAuthor | social network analysis | - |
dc.identifier.url | https://journals.sagepub.com/doi/10.1177/0165551517748289 | - |
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