An approach for preventing the indexing of hijacked journal articles in scientific databases.
Hijacked journals are cloned websites that resemble the homepages of legitimate journals, whose aim is to collect processing and publication fees from unwary authors. There is a growing recognition that the recent proliferation of these scam sites poses a threat to the integrity of the scientific pr...
| Publicado en: | Behaviour & Information Technology Vol. 35; no. 4; pp. 298 - 304 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Apr2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115010093&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115010093 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0144929X B6Q jtl: Behaviour & Information Technology issn: 0144929X maglogo: Y pubinfo: dt: Apr2016 vid: 35 iid: 4 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 115010093 115010093 115010093 10.1080/0144929X.2015.1128975 115010093 ppf: 298 ppct: 6 formats: tig: atl: An approach for preventing the indexing of hijacked journal articles in scientific databases. aug: au: Dadkhah, Mehdi Maliszewski, Tomasz Lyashenko, Vyacheslav V. affil: Department of Computer and Information Technology, Foulad Institute of Technology, Fooladshahr, Isfahan, Iran sug: subj: Abstracting and Indexing Serial Publications Research Fraud Human Access to Information Reference Databases Data Mining Algorithms Decision Trees ab: Hijacked journals are cloned websites that resemble the homepages of legitimate journals, whose aim is to collect processing and publication fees from unwary authors. There is a growing recognition that the recent proliferation of these scam sites poses a threat to the integrity of the scientific process. This study presents an approach intended to prevent the indexing of papers published by hijacked journals in scientific databases by using classification algorithms. We will provide an overview of the problem, define key features of hijacked journals, and present a decision tree that can be used to detect hijacked publications. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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