Publication | Open Access
BIP! Finder
12
Citations
9
References
2019
Year
Unknown Venue
AltmetricsEngineeringInformation RetrievalData ScienceData MiningKnowledge DiscoverySearch EngineBibliometricsBiostatisticsSearch EnginesCitation CountCitation AnalysisArtsContent AnalysisSearch Engine DesignCitation GraphJournalismText Mining
Due to the rapidly increasing number of scientific articles, finding valuable work for further research has become tedious and time consuming. To alleviate this issue, search engines have used citation-based article impact ranking. However, most engines rely on very simplistic impact measures (usually the citation count) and make the problematic assumption that there is a one-size-fits-all impact measure. To address these problems, we present BIP! Finder, a search engine that facilitates the identification of valuable articles by exploiting two different impact measures, each capturing a different aspect of the article impact. In addition, BIP! Finder provides many useful features (article comparison, intuitive visualisations, article bookmarking mechanism, etc.) making it a powerful addition to the researcher's toolbox.
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