Scientometrics: How to perform a big data trend analysis with ScienceMiner

DC ElementWertSprache
dc.contributor.authorFrehe, V.
dc.contributor.authorRugaitis, V.
dc.contributor.authorTeuteberg, F.
dc.contributor.editorPlodereder, E.
dc.contributor.editorGrunske, L.
dc.contributor.editorUll, D.
dc.contributor.editorSchneider, E.
dc.date.accessioned2021-12-23T16:32:52Z-
dc.date.available2021-12-23T16:32:52Z-
dc.date.issued2014
dc.identifier.isbn9783885796268
dc.identifier.issn16175468
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/17560-
dc.descriptionConference of 44. Jahrestagung der Gesellschaft fur Informatik INFORMATIK 2014 - Big Data - Komplexitat meistern - Big Data - Mastering Complexity: 44th Annual Meeting of the Society for Computer Science, INFORMATICS 2014 ; Conference Date: 22 September 2014 Through 26 September 2014; Conference Code:110425
dc.description.abstractThis paper describes the results of the implementation of an application that was designed under the design science principles. The purpose of this application is to identify trends in science. First, the status quo of similar applications as well as the knowledge base about data mining in the field of scientometrics is analyzed. Afterwards, the implementation as well as the evaluation of our application is described. Our web-based application allows to search for contributions (literature and internet, e.g., twitter, news), executes several data mining methods and visualizes the results in seven different ways. Each visualization has some filters and further control elements. It is the first application to provide the complete process from data acquisition to data visualization in an automated way.
dc.language.isoen
dc.publisherGesellschaft fur Informatik (GI)
dc.relation.ispartofLecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
dc.subjectData acquisition
dc.subjectData mining
dc.subjectData visualization
dc.subjectFiltration
dc.subjectKnowledge based systems
dc.subjectVisualization, Control elements
dc.subjectData mining methods
dc.subjectDesign science
dc.subjectKnowledge base
dc.subjectScientometrics
dc.subjectStatus quo
dc.subjectWeb-based applications, Big data
dc.titleScientometrics: How to perform a big data trend analysis with ScienceMiner
dc.typeconference paper
dc.identifier.scopus2-s2.0-84922561860
dc.identifier.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84922561860&partnerID=40&md5=9755d25f768532d3c79781bab7bcfb45
dc.description.volumeP-232
dc.description.startpage1699
dc.description.endpage1710
dcterms.isPartOf.abbreviationLect. Notes Informatics (LNI), Proc. - Series Ges. Inform. (GI)
crisitem.author.deptFB 09 - Wirtschaftswissenschaften-
crisitem.author.deptidfb09-
crisitem.author.parentorgUniversität Osnabrück-
crisitem.author.netidTeFr823-
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